Month: March 2023

A central aim of the original proposal was the concept of a circulating low flow regimen above the reconstituted streambed: “The park design would be centered about a small creek to be reestablished within the right of way by pumping Temescal Creek water to ground level. The reconstituted creek would harmonize with and accentuate the linear nature of the proposed park, providing a focus for lay out of trails, resting spots, and landscaping. The design of park trails would be integrated with the creek and the narrow right or way to achieve a corridor effect inviting the user to walk and experience what the park has to offer. The reconstituted small creek will also serve as a local storm drain by receiving runoff from adjoining properties which have historically drained to the creek”. The other project studied is located in northeastern Ventura County, near the Santa Susanna Pass. Regionally, White Oak Creek is tributary to the Arroyo Simi, which drains the Simi Valley over a distance of approximately 36 miles in a southeasterly direction towards the Oxnard flood plain and Ventura Harbor. The White Oak Creek restoration program was part of a coordinated restoration effort involving a number of developers who have participating in building out housing and other uses within the Douglas Ranch Specific Plan Area. The segment of White Oak Creek comparison study was implemented by Standard Pacific Homes under the regulatory authority of the Corps of Engineers, Department of Fish and Game, and the City of Simi Valley. The restoration program was designed to satisfy two purposes: first, to compensate for the major disruptions to White Oak Creek which resulted from the construction of access roads and flood control measures,indoor growers and to create a common area that functions as both a habitat amenity and as a density buffer and urban design feature within the neighborhoods situated on either side of the Creek.

The Standard Pacific Homes White Oak Creek restoration is immediately linked upstream to a major flood control facility that was built within the Creek’s active streambed boundary in the newly constructed Mount Sinai Memorial Park. To comply with the Clean Water Act, horticultural riparian restoration programs were required for both the Memorial Park and the Standard Pacific residential development. As in the case of the Temescal Creek project, the scope of these restoration projects was clearly flood control, not process driven. The Standard Pacific Homes restoration included a subdivision of land which set aside about three acres of riparian restoration which is served by conducting stored detention waters beneath a manufactured, at grade, “re-constructed” streambed alignment. This reconstructed streambed carries a perennial flow of up to 195 c.f.s. through a diversion from the immediately upstream detention structure . The upstream detention basin gathers both neighborhood street discharge, as well as potential irrigation run-off from the Memorial Park as well as storm water flows.The gradients between the cemetery and residential projects were carefully adjusted and matched. In contrast to the Temescal Creek program, this artificial streambed was designed, disclosed in detail, and is considered a success by both the regulatory agency and the lead agency . Although flood control issues were primary considerations, in this case riparian horticulture restoration and habitat planning were also considered to be of primary importance—unlike Temescal Creek. This is clearly expressed in both the planning efforts and the design. The adjacent development changed ‘Faux’ White Oak Creek from a natural ephemeral channel to a manufactured perennial flow channel. This is a common outcome in southern California restoration projects because most of the time, such projects are designed to incorporate increased continual flows from upstream residential developments.As an amenity, creating a protected common area with habitat functions in a contemporary subdivision is unusual. The reconstructed reach of White Oak Creek now has the character of a young riparian greenbelt. Based on my review of the monitoring records , over the period of monitoring, perennial flow has been provided without interruption into the Standard Pacific Homes restoration area. This site has been under regulatory monitoring for four years.

The monitoring period has been extended beyond the established five-year time frame because of a series of early failures which more frequent monitoring would have revealed. The relative success of each project is compared in Table 1 through a series of defined success criteria. Unlike the outcome at Temescal Creek, for this project, there is a close correlation between original concept and implementation. The low flow diversion has been carefully designed so that it is reliable and operates within the parameters of the source detention waters. The low flow device is calibrated not to rainfall data but to neighborhood runoff flow rates, the actual reliable source of water for the restoration. In this respect, “natural” hydrologic conditions were determined not to be the governing design requirement for long-term success—flow rates out of the upstream neighborhoods were the determinant. The establishment of a firm legal basis for the protection of the restored area, , and the creation of an enclosure around the restoration site have ensured that the surrounding community does not encroach upon the project.Two different strategies of Fe uptake have been described in plants. The so-called chelation strategy , which is mainly found in graminaceous plants, is based on the excretion of phytosideropores to the rhizosphere. Phytosideropores rapidly chelate Fe, to form Fe-PS chelates that are subsequently transported into the root cells through a specific transporter. The so called reduction strategy relies on the coordinated action of a membrane bound Fe reductase, that reduces Fe to Fe, an Fe uptake transporter and an H+ -ATPase that lowers the pH of the rhizosphere, is mainly used by non graminaceous plants, including Beta vulgaris. The reduction strategy includes root morphological, physiological and biochemical changes that lead to an increased capacity for Fe uptake. Morphological changes include root tip swelling, development of transfer cells and an increase in the number of lateral roots, leading to an increase in the root surface in contact with the medium. Some plants are able to accumulate and/or release both reducing and chelating substances, such as phenolics and flavins, which may have a role in Fe acquisition.

Iron has been shown to down-regulate riboflavin synthesis in flavinogenic yeast strains and some bacteria. In plants, Rbfl and derivatives are accumulated and/ or excreted in Fe-deficient roots and could act as a redox bridge for electron transport to the Fe reductase. Moreover, FRO2 belongs to a super family of flavocytochrome oxidoreductases, and a recent study confirmed that the FRO2 protein contains FAD sequence motifs on the inside of the membrane. Also, a connection between Fe deficiency perception and Rbfl excretion has been described to occur through basic helixloop-helix transcription factors in Arabidopsis thaliana. At the metabolic level, increases in the activity of phosphoenolpyruvate carboxylase and several enzymes of the glycolytic pathway and the tricarboxylic acid cycle have been found in different plant species grown under Fe deficiency. Transcriptomic and proteomic studies in Fe deficient plants have also reported increases in root transcript and protein abundances, respectively, of enzymes related to the glycolytic and TCA cycle pathways, among others. Iron deficiency also induces an accumulation of organic acids,danish trolley mainly malate and citrate, in roots. The induction of C metabolism in roots of Fe-deficient plants would not only provide a source of reducing power, protons and ATP for the Fe reductase and H+-ATPase enzymes, but also lead to an anaplerotic root C fixation. Carbon accumulated in roots is exported in the form of organic acids via xylem to leaves, which have otherwise drastically reduced photosynthetic rates when Fe-deficient. The higher energy requirements in Fedeficient root cells are tackled by increasing mitochondrial oxidative processes, and roots from Fe-deficient plants show enhanced respiratory activities and higher O2 consumption rates. On the other hand, the mitochondrial respiratory chain is strongly affected under Fe-deficient conditions, since some of its components are Fe-containing enzymes. Iron deficiency leads to an enhancement of different ROS detoxification strategies. Furthermore, an increase in anaerobic metabolism has also been described in Fe-deficient roots, probably as an strategy to oxidize all the reducing power generated by glycolysis and TCA cycle that can not be easily oxidized in the respiratory chain. When resupplied with Fe, Fe-deficient plants reorganize its metabolism by readjusting metabolic cycles and changing root morphology towards those typical of Fe-sufficient plants. The most common approach used to study Fe deficiency in roots is to analyze only a small number of genes, proteins and/or metabolites. A more comprehensive knowledge of the processes taking place in Fe-deficient roots has been recently provided by the application of modern techniques allowing for the simultaneous and untargeted analysis of multiple genes or proteins. The aim of this work was to characterize the changes induced in the root tip proteome and metabolome of sugar beet plants in response to Fe deficiency and resupply, in order to provide a holistic view of the metabolic processes occurring in plants under different Fe status.The polypeptide pattern of root tip extracts was obtained by 2-D IEF-SDS PAGE electrophoresis. Real scans of typical 2-D gels are shown in Figure 1; an average number of 141 and 148 polypeptides were detected in Fe-sufficient and Fe-deficient plants, respectively .Several causes may account for this discrepancy, including i) protein extraction method and amount of protein loaded in the gels, ii) gel size, iii) pI range and iv) sensitivity of the staining method.

Averaged 2-D polypeptide maps were obtained using gels of three independent preparations, each from a different batch of plants . To better describe polypeptide changes we built a composite averaged virtual map containing all spots present in both Fe-deficient and control root tip extracts . Iron deficiency caused 2-fold increases in 29 spots and 2-fold decreases in signal intensity in 13 spots . Furthermore, 6 spots were only detected in Fe-sufficient plant samples and 13 spots were only detected in Fe-deficient plants . All polypeptides in the composite averaged map are depicted again in Figure 1D, to permit annotation of those polypeptides where identification was achieved by matrix assisted laser desorption ionization – time of flight MS . These polypeptides were labeled from a to v as described in Figure 1D, and homologies found are described in detail in Table 1. From the 29 spots that showed increases in signal in root tip extracts of Fe-deficient as compared to Fe-sufficient controls, the 20 more abundant were excised and analyzed by MALDI-MS. Since the sugar beet genome has not been sequenced yet and few sequences are avail-able in the databases, identification was performed by homology searches with proteins from other plant species. From the 20 spots analyzed, 14 proteins were identified . These include proteins related to glycolysis such as fructose 1,6-bisphosphate aldolase , triose-phosphate isomerase , 3-phosphoglycerate kinase and enolase . Three spots gave significant matches to malate dehydrogenase , and two more polypeptides presented homology with α and β subunits from F1 ATP synthase . Other proteins increasing in root tip extracts from Fe-deficient sugar beet plants as compared to the controls were fructokinase and formate dehydrogenase . Also, one spot gave significant matches to a cytosolic peptidase At1g79210/YUP8H12R_1 . Spot n gave significant match to a glycine rich protein, which possibly has a role in RNA transcription or processing during stress conditions. From the 13 spots detected de novo in proteome maps from root tip extracts of Fe-deficient plants , the 6 more abundant were excised and analyzed by MALDI-MS, resulting in only 2 positive matches . These significant matches were found for glyceraldehyde 3-phosphate dehydrogenase and DMRL .Changes in the amount of DMRL as well as DMRL gene expression and flavin analysis were further studied using root tip extracts of Fe-sufficient, Fe-deficient and Fere supplied sugar beet plants . From the 13 spots showing a decrease in signal intensity in root tip extracts from Fe-deficient plants as compared to controls , 3 were identified by MALDI-MS. Spots q and rgave a significant match to nucleoside diphosphate kinase I and to oxalate oxidase-like germin, respectively.

All vehicles are described by attributes that are common to all of the study vehicles, e.g., range. The attribute levels are varied over several trials to elicit different choices. With these data, econometric models are run to estimate the partial utility values for consumer preferences of each attribute Turrentine and Kurani argue that the underlying assumptions of consumer behavior in many EV Stated preference studies are flawed. These studies assume that the survey respondents have well-formed preferences for driving range, for example. Second, they assume that these preferences remain stable to forecast changes in preferences . Finally, these studies evaluate several vehicle attributes, which study participants have not yet experienced. Consequently, it is very difficult to explore the market for unknown technologies. Demonstration projects can provide a useful platform for examining early reactions and traveler responses to new transportation technologies. In the absence of such field studies, many researchers rely upon Delphi techniques–repeated queries of a panel of respondents–to explore the potential market for ITS technologies. In this evaluation, researchers conducted a modified Delphi evaluation of the market for various ITS technologies to construct the ITS scenarios, which include market penetration estimates, that will be used in the modeling exercise in this study. The modeling results will be used to identify and prioritize a range of ITS technologies on the basis of a set of energy and environmental criteria.Results from ITS operational tests underscore the importance of user acceptance in estimating the environmental impacts of ITS. For example, the SmarTraveler project in Boston found that nearly half of those who used the services changed their travel behavior in ways that could reduce traffic congestion. Nevertheless, system usage remained “too low by any measure to provide noticeable impacts on congestion” . As cited above, Van Aerde and Rakha showed for Orlando’s TravTek that emission impacts were a function of market penetration, 25 liter pot and could even switch from negative to positive depending on market penetration. This section presents an overview of various market penetration estimates that have been made for the ITS technologies examined in this study.

The market penetration results presented here serve as context and comparative points for the estimates we produced in our modified Delphi study. As with the emission studies reviewed earlier, each of these market studies was conducted using differing methods and a variety of ITS descriptions. As mentioned above, One common methodological approach has been the use of Delphi techniques. This technique is designed to facilitate the convergence of the estimates provided by experts.In 1992 the Volpe National Transportation Systems Center was commissioned by the Federal Highway Administration ITS Joint Program Office to develop an analytical framework to predict ITS impacts and assess the potential benefits of ATMS user services. The study focused on ATMS under the premise that it provides the foundation for other types of ITS services. Within the bundle of ATMS services, the study concentrated on ramp metering, signal coordination, integrated traffic management systems, and HOV lanes and ramp meter HOV bypass lanes. The framework integrates a regional planning model with freeway and arterial simulation models, which provide input to emission models, a fuel consumption model, and a safety model. The emission modeling component of the framework uses MOBILE5a and EMFAC7F to provide emission rates for input to EMISSION and EMIS . The EMIS model also provides the structure for applying fuel consumption rates to link-based data. The fuel consumption rate model used for this study was developed by the Caltrans Office of the Transportation Laboratory in cooperation with the US DOT and the FHWA . A new safety model was developed specifically for the framework, incorporating safety factors that were determined from historical accident data for the study corridor. The US DOT framework generates a set of MOEs that can be used to evaluate the impact of implementing ATMS user services. The MOEs are categorized under four major impact areas: congestion or operational measures; emissions; fuel consumption; and safety. No attempt was made to distinguish between supply- and demand-related impacts as in Brand . The framework was applied to model five alternative ATMS scenarios and the results were compared to those for a baseline configuration. The scenarios were made up of various combinations of fixed time and demand-based signal coordination with fixed time and synchronized freeway ramp metering.

A summary of the findings of these analyses are presented in the section of this report titled “Quantitative Assessment: Modeling Studies.”Brand describes an evaluation framework that is designed to be sensitive to the differences between ITS and traditional transportation improvements. An extensive set of evaluation criteria is presented, distinguishing between the supply and demand impacts of ITS deployment. The criteria are categorized into five main impact types. The first two criteria types, increased operational efficiency and increased output , are separated to avoid the possibility of dramatically underestimating the benefits of a given technology. These criteria are also structured in a second dimension explicitly to address the time frame of the impacts . The additional criteria types are safety, energy and environmental, and implementation impacts. Brand shows how the full set of criteria can be grouped to avoid double-counting of benefits because of the correlations that exist between certain criteria. An example also demonstrates how evaluation criteria can be weighted to allow the evaluator to produce an overall weighted measure of merit for each project. Finally, Brand provides default values to evaluate ITS improvements for inclusion in transportation system plans.Lo et al. developed a framework for comparison of dynamic traffic models, emphasizing the dimensions of functionality, traffic and route choice dynamics, and overall network performance. The framework is set up to compare the models against a check-list of functions and also to compare the ability of each tool to model twelve scenarios developed for five different test networks. The report provides a list of performance measures to be determined for each modeling tool and a discussion of how the results are to be interpreted. The comparison framework is designed to be generic and permit comparison of many traffic models. However, four specific models were selected for comparison in this study: INTEGRATION, DYNASMART, DINOSAUR, and METS. The comparison results and the impact of perturbations to O-D data will be presented in Part II and III of the report, which are almost complete. Some of the traffic simulation tools mentioned above are capable of estimating the energy and environmental impacts of the simulated traffic conditions . Others can provide output suitable for input to some fuel consumption and emission models. However, raspberry cultivation pot modeling frameworks that provide output suitable for average speed based emission models such as the US EPA MOBILE and the California Air Resources Board EMFAC models are not capable of providing accurate assessments of the environmental impacts of the ITS scenarios being considered.

The MOBILE and EMFAC emission factors predict vehicle emissions based in part on average trip speeds and a large number of FTP bag emission measurements. These models are intended to predict regional emission inventories, and hence they are not adequate for evaluating microscopic-level operational improvements, such as those achieved by ITS strategies. To evaluate the emission benefits of such systems, it is necessary to employ an emission model that considers the modal operation of a vehicle . The INTEGRATION and DYNASMART models make use of modal emission models that account for microscopic changes in vehicle speed profiles and Ramachandran , respectively. A brief summary of these models is presented in the sections below .Much has been written about the capabilities of the INTEGRATION traffic simulation model . This section presents some of the aspects of this model that are relevant to our research. For more detailed information about the model development, capabilities, limitations, and applications, the reader is referred to the reports just mentioned and the INTEGRATION User’s Guide . The INTEGRATION traffic simulation model was developed by Michel Van Aerde of Queen’s University in Ontario, Canada . This microscopic simulation model was developed with the purpose of simulating integrated networks composed of freeways and arterial roads, with a particular emphasis on modeling ITS scenarios. INTEGRATION 2.0 simulates the behavior of individual vehicles on signalized arterial and mainline freeway links, with the ability to model merges, diverges, and weaving sections. The model contains algorithms to simulate many aspects of traffic behavior including: lane changing; link-to-link lane transitions; car following; route selection and traffic assignment; signal cycles,including turning movements, shock waves, over saturation delay, and gap acceptance at traffic signals; signal coordination; stop and yield signs; and incidents and diversions. INTEGRATION also provides estimates of effectiveness measures for individual vehicles; links; O-D pairs; and complete networks, including link travel time, fuel consumption, and vehicle emissions.The revised ozone standard is intended to replace the current one-hour standard with an eight-hour standard. However, the one-hour standard will continue to apply to areas not attaining it for an interim period to ensure an effective transition to the new eight-hour standard. Title I of the CAA addresses the requirements for different classifications of non attainment areas that do not meet the current one-hour standard . These requirements include such items as: 1) mandatory control measures, 2) annual rate of progress requirements for emission reductions, and 3) offset ratios for the emissions from new or modified stationary sources. These requirements have contributed significantly to the improvements in air quality since 1990. Based on the US EPA’s legal review, the Agency has concluded that Title I should continue to apply as a matter of law for the purpose of achieving attainment of the current one-hour standard. Once an area attains the one-hour standard, those provisions will no longer apply and the area’s implementation of the new eight-hour standard would be governed only by the provisions of Title I. To streamline the process and minimize the burden on existing non attainment areas, the one-hour standard will cease to apply to an area upon a determination by the US EPA that an area has attained air quality that meets the one-hour standard.

In light of the implementation of the new eight-hour standard, which is more stringent than the existing one-hour standard, States will not have to prepare maintenance plans for those areas that attain the one-hour standard. For areas where the air quality does not currently attain the one-hour standard, the one-hour standard will continue in effect. The provisions of Title I would also apply to designated non attainment areas until the time each area has met the one-hour air quality standard. At that time, the US EPA will take action so that the one-hour standard no longer applies to such areas. In any event, the “bump-up” provisions of Subpart 2, of Part D of Title I, which require that areas not attaining the standard by the applicable attainment date be reclassified to the next higher classification, will not be triggered by the failure of any area to meet the new eight-hour standard. The purpose of retaining the current standard is to ensure a smooth legal and practical transition to the new standard .For areas that attain the one-hour standard but not the new eight-hour standard, the US EPA will follow a flexible implementation approach that encourages cleaner air sooner, responds to the fact that ozone is a regional as well as local problem, and eliminates unnecessary planning and regulatory burdens for State and local governments. A primary element of the plan will be the establishment under Section 172 of the CAA of a special “transitional” classification for areas that participate in a regional strategy and/or that opt to submit early plans addressing the new eight-hour standard. Because many areas will need little or no additional new local emission reductions to reach attainment, beyond those reductions that will be achieved through the regional control strategy, and will come into attainment earlier than otherwise required, the US EPA will exercise its discretion under the law to eliminate unnecessary local planning requirements for such areas. The US EPA will revise its rules for new source review and conformity so that States will be able to comply with only minor revisions to their existing programs in areas classified as transitional.

High root expression of GS1 in these fields indicates that root N assimilation was elevated and thus actual plant N availability and uptake was higher than low inorganic N pools would suggest . Fields from group 2 demonstrated N surplus, showing similar yields to group 3 but with lower total and labile soil C and N and a higher potential for N losses, given much higher soil inorganic N . While actual N losses depend on a host of factors , high soil NO3 – is considered an indicator for N loss potential. Results from a companion study support the idea that soil microbes were C rather than N-limited in these fields, showing higher potential activities of C-cycling soil enzymes but low activities of N-cycling soil enzymes, the inverse of group 3 . An alternative multivariate clustering approach based on an artificial neural network suggests multiple potential drivers of higher inorganic N pools in these fields, including both management factors and soil characteristics . For instance, field 4 had strong indications of surplus N driven at least in part by a large application of seabird guano , a readily-mineralizable organic N fertilizer, at tomato transplanting when plant N demand is low. In contrast, higher inorganic N in field 8 was likely driven by low plant N demand based on very low soil P availability, which resulted in plant P limitation. These site-specific problems were identifiable due to the focus on variability across similar organic fields and illustrate the need for site-specific approaches to reduce N losses. Finally, the two fields included in group 1 were exemplary of N deficiency, in which low N availability compromises crop productivity but also likely limits N losses within the growing season. While low soil NH4 + and NO3 – concentrations were similar to group 3, low total and labile soil organic matter and poorly-timed organic matter inputs compromised microbial activity and likely limited N mineralization.Cytosolic glutamine synthetase GS1 encodes for the enzyme that catalyzes the addition of NH4 + to glutamate,fodder systems for cattle the former resulting from either direct uptake of NH4 + from soil or reduction of NO3 – in roots.

GS1 is thus the gateway for N assimilation in roots and is upregulated to increase root N assimilation capacity. Similar levels of GS1 expression in groups 2 and 3, in spite of large differences in soil NH4 + and NO3 – concentrations at the anthesis sampling, suggests that plant N availability is indeed higher in group 3 fields than would be expected based on measurement of inorganic N pools alone. The low levels of GS1 expression found in fields with clear N deficiency supports this idea. These results complement recent experimental approaches that showed rapidly increased expression of GS1 in tomato roots in response to a pulse of 15NH4 + -N on an organic farm soil, which was linked to subsequent increases in root and shoot 15N content, even when this pulse did not significantly change soil inorganic N pools. GS1 transcripts and glutamine synthetase enzyme activity also increased with increasing NH4 + and NO3 – availability in sorghum roots, suggesting this response may be widespread among plant species. Interestingly, inclusion of soil GWC in multiple linear regression models increased the proportion of GS1 expression variability explained to nearly 30% ; soil water content increases microbial activity as well as the mass flow and diffusion of inorganic N to roots. Further research will undoubtedly show how other factors like crop physiological N demand relative to C fixation and P availability increase the interpretability of N uptake and assimilation gene expression in roots.The N cycling scenarios identified on this set of organic fields corresponded at least in part with landscape clusters based on landscape and soil characteristics . Fields that balanced high yields with low potential for N loss and high internal N cycling capacity were part of PAM cluster 1, which had the highest productive capacity rating . Landscape clusters encompassing more marginal soils included both low-yielding fields exhibiting N deficiency or high-yielding fields that used inputs of highly available N like seabird guano to alleviate N deficiency . But these inputs led to the highest soil NO3 – levels and thus came at the cost of higher potential for N loss. Long-term efforts to increase internal soil N cycling capacity would help alleviate both N deficiency and the need for such large inputs of labile N. Whether farmers are willing to invest in management to increase soil N cycling capacity depends in part on how likely they perceive the benefits to be, especially on marginal soils.

The discussions that we had with each farmer in this study indicated genuine interest in adaptive management to further tighten plant-soil N cycling, but this may not always be the case. Indeed, the proportion of management vs. inherent soil characteristics responsible for driving differences in N cycling is challenging to untangle. Farmers may allocate more resources to more productive land and likewise fewer resources to more marginal land, or may selectively transition more marginal land to organic management. Documenting the multiple services provided by increases in soil quality and facilitating information exchange among organic growers such as through the landscape approach used here may help build momentum for efforts to improve soil quality and plant-soil-microbe N cycling.Net tropical forest loss of 7 million hectares per year occurred between 2000 and 2010, with conversion to agriculture accounting for 86% of deforestation . Annual deforestation in tropical Asia during the 1990s reached up to 5.6 million ha yr−1 , resulting in the emission of 1.0 Pg C yr−1 to the atmosphere . In Indonesia, the total forest area of 117 million ha in 1990 dropped to 89 million ha in 2011–2012 with primary, secondary and plantation forests occupying 45.2, 40.8 and 3.0 million ha, respectively . The average forest loss of 1.3 million ha yr−1 from 1990 to 2012 resulted from burning and conversion to agriculture, mining and infrastructure with Indonesia contributing to ∼10% of total global forest loss each year. Short-term changes in soil properties following conversion of tropical forests to agricultural land use are often pronounced and in most cases detrimental to sustainable agricultural production. In contrast to the Amazon rainforests supported by Oxisols and Ultisols , Indonesia’s rainforests are largely supported by volcanic soils, primarily Andisols. These Andisols support high agricultural productivity with some of the world’s highest human-carrying capacity being found on volcanic soils in Indonesia . With respect to greenhouse gases, fodder sprouting system Andisols are notable for having the highest soil carbon storage capacity among the mineral soil orders in temperate and tropical climatic regimes with an average carbon stock of 25.4 kg C m−2 . Matus et al reviewed soil carbon storage and stabilisation in andic soils and concluded that the most important mechanism of sorption of soil organic matter by short range ordered amorphous minerals is the ligand exchange.

While short-term changes in properties of tropical rainforest soils have been extensively studied, there is a paucity of information concerning long-term changes in soil properties resulting from changing land use and management practices, especially with respect to Andisols. Greenhouse gas emissions from agriculture are reported to contribute up to 30% of anthropogenic emissions . Soils can be a major source or sink of GHG from terrestrial ecosystems depending on the ecosystem disturbance regime and soil management practices. Soil carbon storage is dependent on soil mineral constituents, with volcanic ash soils typically having exceptionally high potential C stocks owing to their high content of active Al and Fe constituents . In Andisols, Chevallier et al. showed organic matter transformation to CO2 via microbial respiration was lower as allophane content increased. In addition, changes in land use/land cover alter organic matter quantity and quality, which are major factors controlling soil microbial biomass and activity . Given the high C stocks in Andisols, it is important to assess the fate of soil C following land-use conversion from forest to intensive agricultural production, especially with regard to rapid deforestation in the tropics. Andisols have several unique properties that affect agricultural productivity, such as high P fixation, high organic matter concentrations, a clay-size fraction dominated by pH dependent variable charge, low bulk density, high porosity, high water retention capacity and high mesopore content . In particular, high P retentionin Andisols can limit agricultural productivity by limiting plant availability of P. Currently, there is little information on how P retention and availability in tropical Andisols change with different land use and agricultural practices. Nitrate leaching characteristics in Andisols are also strongly affected by variable charged constituents as positive charges can retain nitrate enabling higher plantutilization efficiency. In southern Chile, Huygens et al. reported NH4 + and NO3 − retention of 84 and 69% of N fertilizer additions, respectively, after one year based on 15N pool-dilution and 15N tracer studies of forested Andisols. In Japan, the maximum nitrate adsorption by Andisols ranged from 0.4 to 7.0 cmolc kg−1 with the highest values occurring in soil horizons with high allophane content and low organic carbon content . Furthermore, Deng et al. evaluated the denitrification rates from eight Andisols under three different cropping systems in an intensive livestock catchment of central Japan and reported that N loss via denitrification from upland fields was almost negligible in spite of substantial N inputs . In addition to retention of NO3 − by positively charged colloids, a laboratory study by Matus et al. reported high retention of NO3 − in Andisols through transformation of NO3 − to dissolved organic nitrogen . In Indonesia, land use/land cover of Andisols is primarily native rainforest, tea plantation, horticultural crops, terraced paddy fields and other food crops. Land-use conversion from tropical rainforest to agriculture has taken place over long periods of time ; however, no rigorous studies have examined changes to Andisol soil properties over these time periods. In addition, several studies have examined microbial biomass carbon and CO2 measurements in topsoil horizons, however, MBC and CO2 measurements in subsoil horizons have been ignored although these measurements are crucial for explaining the exceptionally high carbon stocks in Andisols. Given the several unique properties of Andisols, it may be expected that these soils are more resilient to land-use change and agricultural management practices. Therefore, we hypothesize that the unique soil properties of Andisols lessen the negative impacts of land-use change from tropical forest to agriculture on soil physical, chemical and biological properties. The objective of this study was to take advantage of long term, land-use/land management changes to examine changes in several physical, chemical and biological properties of Andisols in tropical Indonesia following conversion of rainforest to tea plantation and horticultural crops.Samples were pretreated with H2O2 to remove organic matter and dispersed with dilute Na-hexametaphosphate. Silt- and clay-sized fractions were measured after sedimentation according to Stokes law. The sand fraction was separated from the clay and silt fractions by wet sieving through a 0.05 mm sieve. Water retention at various tensions was determined using a pressure plate. Plant-available water holding capacity was estimated as the volume fraction of water retained between 33 and 1500 kPa. A sample of < 2-mm , air-dry soil was placed on a porous ceramic plate and wetted by capillary action; gravimetric water content was measured following attainment of equilibrium at 33 and 1500 kPa. Soil pH was measured 1:2 in H2O and 1.0 M KCl. Phosphate retention was determined using the method of Blakemore et al. and the Bray-1 extraction was used as an estimate of available P . Exchangeable cations were displaced by 1 M NH4OAc at pH 7.0, then the cations were measured in the supernatant using an atomic absorption spectrometer . The cation exchange capacity was determined in 1 M NH4OAc after extraction of NH4 + by 10% NaCl as a measure of CEC. Base saturation was calculated as the sum of base cations by 1 M NH4OAc divided by CEC. Sulfate-sulfur was extracted using monocalcium phosphate as outlined by Schulte and Eik and available micronutrients were determined by DTPA extraction . All weight percent data were reported on an oven-dry basis .

Instead, a single insertion event is approved for commercialization and then must be transferred via standard back crossing to other varieties. This is highly inefficient and often makes it difficult to regain the unique properties of all the diverse varieties.The IR-4 program could also assist with chemical residue testing and with other aspects of meeting the regulatory requirements for release of transgenic horticulture.Leaves growing in sunny locations have comparatively high photosynthetic capacities, Rubisco activity, rates of electron transport, and rates of dark respiration . Some species are restricted to sunny or shady locations, and the leaves of these plants are often genetically adapted to their characteristic light environment. The leaves of other species, including those that are naturally exposed to particularly variable light environments, acclimate to local conditions . Acclimation to extended changes in light enhances net assimilation and nitrogen use efficiency while decreasing vulnerability to high light stress .The local light environment influences the morphological development of leaves in many species, resulting in comparatively thick leaves in bright locations . Fully expanded leaves have a limited capacity for morphological change , and acclimation by these leaves requires biochemical changes in carboxylation, electron transport, and light harvesting, as well as modifications to chloroplast structure and orientation . Monocotyledons with basal meristems, long leaves, and dense canopies may represent a case where photosynthetic acclimation by biochemical change is particularly advantageous. The grass Lolium multi-florum exhibits a strong capacity for local photosynthetic acclimation along the length of a leaf . The leaves of plants like Lolium are produced in dark or dim conditions at the base of plants, and, over time,dutch bucket hydroponic are pushed to the upper part of the canopy. Typha latifolia , at all monocot that forms dense and highly productive mono specific stands in wetlands , may provide an even more extreme example. T. latifolia ramets originate from rhizomes that are buried in sediment, submerged under water, and often shaded by a dense layer of litter and existing plants.

Initial leaf growth is supported by carbohydrates that are either mobilized from rhizomes or translocated from older leaves. Depending on sediment thickness and water depth, and the density of the litter layer and existing canopy, the lower 50–100 cm of a Typha leaf may experience almost total darkness . These characteristics make Typha a useful experimental system for investigating the acclimation capacity of morphologically mature leaves. Basal growth in Typha allows the separation of leaf age from light environment; the oldest segments of Typha leaves are exposed to the brightest light, as opposed to plants with apical meristems, where the youngest leaves are in bright conditions. We investigated the photosynthetic capacity of T. latifolia leaves over time following step changes in shading at different locations along leaves. We hypothesized that morphologically mature Typha leaves have a strong ability for local acclimation, and that individual leaf segments acclimate to the local light level autonomously from the rest of the leaf.Two-month-old sun and shade grown plants with several fully expanded leaves were placed on a bench under high light, and a pair of fully expanded leaves from each plant were selected for experimentation. Individual leaf segments between 20 and 45 cm from the tip were exposed to either sun or shade during the 15-day transfer experiment using cylinders of 80% neutral shade cloth, creating the full combination of segments exposed to constant low light , constant high light , low to high light , or high to low light . Additionally, a set of segments on the same leaves were exposed to either constant high light or low to high light . All treatment combinations and locations were replicated six times. The photosynthesis rate under bright light , stomatal conductance and dark respiration rate were measured every two or three days for two weeks in the middle of the sun and shade segments , on six replicate plants using a portable gas exchange system . Afull sun was measured at a PPFD of 2000 mol m−2 s−1 and Rd was measured in darkness after allowing 3–5 min for equilibration. Leaf temperature was controlled at 25 ◦C and reference CO2 concentration at 370 mol mol−1. The leaf to air vapor pressure deficit ranged from 0.6 to 1.5 kPa. Photosynthetic light response curves were measured after leaves had fully acclimated to a change in light .

A full sun was calculated as the photosynthetic rate at 2000 mol m−2 s−1; Amax was calculated by extrapolating the regression to infinite light; Rd was calculated as the y-intercept; the apparent quantum yield was calculated as the slope extrapolated to darkness. The light response curves were started at high light , and assimilation was measured in response to stepwise PPFD decreases until full darkness. Stomatal conductance decreased gradually in response to light decreases, and increased gradually in response to light increases. This sluggish stomatal response either led to lower rates of photosynthesis for light curves run from dim to bright conditions relative to curves run from bright to dim conditions, or forced unreasonably long equilibration times. Moreover, midday field and greenhouse observations showed that leaves exposed to a continuous PPFD of 2000 mol m−2 s−1 for ∼15 min exhibited a steady CO2 assimilation. We therefore opted to carry out light curves from bright to dark conditions, but acknowledge that lags in stomatal adjustment may have resulted in somewhat higher Ci for the light curves than would have been observed for fully equilibrated leaves. Nonetheless, we emphasize that our study is comparative, and the key is consistency across treatments; we executed the light curves the same way for all treatments and leaf segments. Nitrogen concentration , and leaf mass per area , were measured on the leaf segments used for gas exchange. Nitrogen was determined using the micro Kjeldahl technique; samples were oven dried, ground in a Wiley mill, weighed, digested, and nitrogen concentration was determined with an auto analyzer .We characterized the vertical gradients of light and photosynthetic characteristics during midday sunny conditions in August 2004. The PPFD profile was measured through the canopy at 48 different locations in the SJFM using a horizontal quantum sensor mounted on a 2 m handheld pole. Each profile consisted of ten individual measurements recorded with a datalogger at 0.0, 0.6, 1.2, and 3.0 m above the sediment surface. The 3.0 m measurement was above the canopy. LAI was measured at the base of the canopy with a LI-COR LAI-2000, assuming non-clumped leaves and without distinguishing between live leaves and litter. Photosynthetic light response curves were measured on three segments of fully expanded leaves from 5 different plants. The cross section of leaves changed from flat at the tip to triangular at the base, and it was not possible to seal the chamber on leaf segments further than 100 cm from the tip.The parameters derived from the light response curves, the nitrogen content, and the leaf mass per area,dutch buckets system were compared between treatments using Univariate ANOVA or t tests.

The effect of light treatment was analyzed by Student’s t-test. Univariate ANOVAs and Tukey tests were used to compare Afull sun, Amax, gs and Rd between the light treatments within each sampling period. The effects and interactions of treatment and time following transfer were analyzed with multivariate analysis of variance ; this analysis corrected F values due to temporal auto-correlation. MANOVA does not require the response variables to be equally correlated, assuming an unstructured variance–covariance matrix . The effect of leaf position on the photosynthetic parameters of leaves growing in natural conditions was analyzed with three paired t-tests, because of the high variation among leaves. Statistical analyses were performed with JMP software version 7.0 and Minitab statistical software version 15.Our results confirm previous reports that species from highly variable light environments have a strong capacity for photosynthetic acclimation. In the case of T. latifolia, light heterogeneity is created by the combination of a basal meristem and a dense canopy of live leaves and litter . Typha leaves are exposed to markedly different light environments as they grow and individual segments are pushed upward . The upper segments of leaves in the field, which occurred in a brighter environment, had higher rates of CO2 uptake . Previous field studies on T. latifolia have also reported large CO2 assimilation and gs gradients along leaves . We hypothesize that the patterns of leaf photosynthesis and conductance in Typha reflect four properties. Mature Typha leaf segments are morphologically preformed to function in high light and allow high rates of Afull sun, regardless of the current or growth environment. Mature Typha leaf segments contain sufficient amounts of nitrogen to support high rates of Afull sun, regardless of the current or growth environment. Mature Typha leaf segments rapidly reallocate nitrogen between active and inactive pools in response to local light availability; acclimation occurs at a local level and does not require nitrogen translocation into or out of a leaf segment. The controls on stomatal conductance remain constant over time; the patterns of conductance can be explained based on simple, short-term adjustments that act to maintain a nearly constant Ci concentration despite the changes in Afull sun and the physical environment. We interpret these patterns as a highly plastic strategy that maximizes carbon gain by a monocot growing in a vertically heterogeneous light environment. The construction of leaves that are morphologically capable of high rates of Afull sun is a simple consequence of the spatial decoupling of the growth environment from Fig. 5. Midday photosynthetic photon flux density at 0, 0.6, 1.2, and 3.0 m above the soil surface at the San Joaquin Freshwater Marsh . The lower three locations were within the canopy; the 3.0-m observation was above the canopy. Typha latifolia light response curves measured at the SJFM as a function of distance from the leaf tip . Each curve is the mean ± 1 standard deviation of 5 curves on different plants. The continuous line is the best-fit non-rectangular hyperbola. that experienced later in life. The strategy of investing in leaves that have a morphological capability for high rates of CO2 uptake appears advantageous given a situation where it is difficult to predict which leaves will ultimately experience high light conditions, and where fully expanded leaves are unable to morphologically adjust to a change in light. High rates of Afull sun come at the cost of high Rd. A leaf with a low Afull sun in a shady site has a more favorable carbon balance than a leaf with a high Afull sun in the same environment; the carbon savings associated with reduced Rd more than offset the loss of potential photosynthesis during occasional sunflecks. The rapid down regulation of Afull sun following transfer to shade would be expected to improve the C balance of leaf segments by decreasing Rd. The initial changes in Rd following light change were probably tied to the changes in leaf photosynthetic activity, and the energy requirements to process and export carbohydrates, as well as changes in protein turnover . Subsequent changes in Rd may have been associated with changes in the biosynthesis and/ordegradation of cellular components, such as Rubisco, cytochrome f, and chloroplast ATPase . The amount of nitrogen in leaf segments remained nearly constant over time, leading us to hypothesize a fraction of the nitrogen in shaded segments is stored in inactive pools and is rapidly activated following transfer to high light. These changes may include adjustments in partitioning among carboxylation, electron transport and light harvesting, chloroplast ultra structure, volume, and orientation . The high N content of shaded segments should not be viewed as wasteful. These nutrients can be reabsorbed and reallocated to the rhizome during senescence; a high reabsorption efficiency of P and N has been reported for Typha dominguensis . Moreover, this strategy allows a leaf segment to rapidly and autonomously respond to a change in light availability, without importing or exporting nitrogen to or from other leaf segments or organs.Plants are the primary producers on earth, assimilating carbon dioxide by daytime photosynthesis for the biogenesis of all essential structures. This carbon assimilate is partitioned primarily into sugars and starch in the autotrophic ‘sources’ with a portion of the sugars allocated to the heterotrophic ‘sinks’ to support growth of the latter.

A cross-species comparison of environmental associations suggests some similarities in the genetic mechanisms involved in climatic tolerances across conifer genera. For each of four European conifer species in the Italian Alps, 6–18 SNPs were associated with precipitation/temperature PC axes . There was some overlap between species in the genes represented, including heat shock proteins, and cell wall construction and carbohydrate metabolism genes .Gene expression studies have identified a range of genes that may be involved in drought responses, but these results are not easily connected to the results of physiological or provenance response studies. First, RNA transcripts reflect the genes being expressed at a particular instant, whereas morphological or physiological traits are the result of processes acting over a longer time. Second, most gene expression studies do not examine differences between populations. Although some evidence suggests that stronger gene expression changes during stress are associated with greater growth or survival, different genotypes and demographic stages can show significant differences in gene expression changes . A few studies have begun to address this. Provenances of P. pinaster differed in the expression response of two dehydrin genes, as well as in physiology and mortality rates . Similarly, three genotypes of P. taeda differed in their gene expression responses to drought and re-watering . More such studies are needed, but care must be taken to distinguish between drivers of expression differences. For instance, a more drought-sensitive tree might express higher levels of dehydrins at a given drought stage because the leaf water potential has dropped faster than in a drought-resistant tree, whereas the resistant tree might express higher levels of dehydrins than the sensitive tree at a given leaf water potential.

Genome scan and G2E association studies can be useful tools in the search for genes responsible for local adaptation. Although such studies can identify loci at which allele frequencies differ between environments,nft system it is not always clear how these differences are connected to phenotypic differences, and thus what traits are under selection in a given environment. This is where QTL and G2P association studies are useful.Most conifer QTL studies have focused on wood traits, growth or yield. Of the two that have examined drought tolerance, the first identified four significant and four suggestive QTLs for d13C in P. pinaster, none of which co-located with QTLs for ring width . The second examined a wider range of traits – photosynthesis , chlorophyll fluorescence, gs, d13C, intrinsic WUE and specific leaf area – in F1 cross seedlings of P. pinaster when well watered or after 1 or 2 wk without water, and identified 28 significant and 27 suggestive QTLs . Locations of the QTLs for each trait varied by time point. Candidate genes within the QTLs were identified : those for gs and WUEi included stomatal regulation, ABA signaling and cell wall construction genes; those for d13C included an aquaporin; and those for chlorophyll fluorescence included transcription factors and a histone chaperone.However, only a few studies have investigated drought tolerance in conifers , with less success. All such studies used d13C as the focal trait. As we argue in Section VI, other traits would probably yield results that are more helpful for the understanding of drought responses. Gonzalez-Martinez et al. examined 41 candidate stress response genes of P. taeda, using 61 tree families planted at two sites. However, drought stress was probably mild, and they only identified one strongly associated gene and one weakly associated gene at each site. A later study on the same species examining 3938 SNPs identified seven new associations with d13C . Four of the associations were with unknown proteins, with only a transcription factor probably involved in the ABA-mediated stress response having an obvious connection to drought responses. G2P and G2E association studies complement one another, with the first identifying loci linked to targeted traits, but not whether these loci are under selection in nature, and the second doing the opposite.

The combination of these approaches is useful for the identification of genes and traits under selection in natural settings, but so far few studies have taken this approach. Eckert et al. tested the association of SNPs with five phenotypic traits and 11 environmental variables across 10 P. lambertiana populations around Lake Tahoe. This study identified six genes associated with phenotypic traits , and 31 associated with environmental PCs. Two genes were associated with both a trait and an environmental axis, including a glucose transport protein associated with d13C and environmental variables linked to water availability. A study focusing on multiple drought response traits and a larger number of SNPs might be able to identify more genes that have variants associated with both environmental gradients and drought tolerance traits. Some traits and processes involved in drought response have been better studied at the genetic level than others . Provenance studies have indicated that differences in stomatal control and shoot growth are often involved in local adaptation to drought, and all other study types have identified the genes likely to be involved . However, although root growth has also been identified as important by provenance studies, root-growth-related genes have not been identified. Conversely, although genes related to resistance traits, such as changes in carbohydrate metabolism, and protective and pathogen defense molecule production, have been identified in expression or association studies, these traits have been largely ignored in provenance studies. Finally, xylem traits, including refilling ability, have not been the focus of any genetic study type.Tree improvement programs that aim to increase growth potential and stress resistance face the challenges of long generation times, the need for large-scale field experiments and the late expression of traits such as wood density . Genomic selection, already routinely used in livestock breeding, has been proposed as a method of speeding up this process by using marker-predicted breeding values for phenotypes of interest . This approach is suitable for species with low LD and for traits with complex genetic architectures as it uses thousands of markers with effects that are estimated simultaneously . As with traditional phenotypic selection, accuracy is likely to be greatest when tests are carried out in environments similar to the target environment, because of the high likelihood of geno type 9 environment interactions .

Several recent studies have demonstrated the potential of genomic selection approaches for traits of interest to forestry. Resende et al. carried out an early evaluation of genomic selection in P. taeda, making use of clonally replicated individuals grown on four sites and genotyped at 4825 SNPs. They found that the accuracy of prediction models within sites ranged from 0.63 to 0.75 for diameter and height,hydroponic gutter and estimated that the breeding cycle could be speeded up by 50% with this method. Gamal El-Dien et al. used GBS to genotype over 1000 interior spruce trees over three sites that had been pheno typed for yield and wood attributes, and found that the incorpo ration of genomic information produced more accurate heritability estimates. Genomic estimated breeding values were most accurate when data from multiple sites were used to fit the model. Of even more relevance to selection for drought tolerance, Jaramillo-Correa et al. identified 18 SNPs associated with climatic PC axes in P. pinaster, and found that the frequency of locally advantageous alleles at these loci correlated with population level survival rates in a common garden at the hot/dry end of the species range. Together with the growth trait analyses, these results suggest that association techniques could be applied to predict breeding values for overall drought tolerance or particular drought tolerance traits even though only some of the loci involved have been identified. There is evidence of significant potential for selection approaches to improve drought responses in conifers. Provenance studies have shown evidence of genetic differentiation between populations in drought responses, and genome scan and G2E associations are finding evidence of natural selection on within-species genetic variation. Second, heritabilities for drought tolerance traits, when these have been examined, tend to be moderate to high. The calculation of heritability requires pedigree information: parent– offspring or sibling and half-sib comparisons. Narrow-sense heritability is the fraction of the variance in a trait attributable to additive genetic variation, as opposed to environmental and non additive genetic variation. Because heritability depends on both genetic variation in the population assessed and the degree of variation caused by the environment, estimates are not transferable between situations. In P. pinaster, estimates of d13C narrow-sense heritability ranged from 0.17 to 0.41, depending on how many individuals of what populations were assessed in what sites; and ring width and height growth rates were also moderately heritable . In the same species, heritability of P50 was 0.44, but this was driven more strongly by low levels of other sources of variation rather than high additive genetic variation . Across species, measured heritabilities for d13C range from the very high 0.7 for Araucaria cunninghamii to < 0.1 for P. taeda . Managers of wild forests are often focused on ensuring the resilience and function of the ecosystem rather than productivity. G2E and G2P association studies may help to identify seed sources that could be ‘preadapted’ to projected conditions for replanting in wild lands. However, wild trees face a range of challenges, including disease and competition, as well as drought . Stand structure and soil properties may also directly affect how trees experience drought stress. Studies that integrate stand level processes with genetic testing can further bridge gaps between genetic experiments and forest-scale management. Restoration projects could be used as experiments to test genomic predictions of survival and growth in a given environment, as well as the effects of genetic composition and diversity of the planted population on restoration success.

Common garden, gene expression and genetic association studies all have different strengths and weaknesses, and none alone will answer the question of how genetic differences affect drought tolerance . As described previously, a combination of different types of association study may help to identify loci that are under selection in the wild and the traits they influence. Similarly, gene expression studies could easily be combined with common garden studies of adults or seedlings to address whether differences in drought responses between populations or genotypes are a result of differences in gene sequences, gene expression patterns or both.Many studies to date have focused on WUE, often using d13C as a proxy. As discussed above, however, WUE is a ratio of changes in photosynthesis and transpiration, which can both vary, and higher WUE may or may not be associated with greater survival or growth in dry conditions. Moreover, different measures of WUE are not entirely consistent. We therefore recommend that future studies use survival and/or growth during and following drought as the metric of overall ‘drought tolerance’, and measure photosynthesis and water loss separately if these are processes of interest. The time involved in the measurement of traits for hundreds or thousands of individuals has encouraged the focus on easily measured d13C, but much progress has been made in high-throughput phenotyping techniques . For instance, thermal and long wave infrared sensors can measure leaf temperature or stomatal conductance, near and short-wave infrared sensors can measure leaf water content, and fluorescence sensors can measure chlorophyll content and photosystem efficiency .There are several traits and processes that have been suggested to be important for drought response by physiological studies, but about which there is little genetic information . Genetic studies frequently identify genes related to carbohydrate metabolism and transport as having altered expression or allele frequencies depending on water availability. It is difficult to make sense of these patterns because the link between these metabolic changes and tree function and survival during drought is still unclear. We also know relatively little about which species can refill cavitated xylem, under what circumstances and by what mechanisms. Thus, it is difficult to determine whether any genes identified by expression or G2E studies are involved in this process. Similarly, how roots and root growth respond to changes in water availability, and what genes are involved in these responses, remain poorly understood. Although the measurement of root architecture can be complex, high-throughput methods are being developed for this as well .Most experimental studies, including those looking at gene expression, have focused on seedlings.

The first target analyzed is human butyrylcholinesterase , an enzyme that can act as a bio-scavenger to counteract the effects of cholinesterase inhibitors such as sarin and that is a candidate for bio-defense countermeasures in several countries. While this product would encounter market dynamics that are different from other commercial products, it is nevertheless designed to satisfy an important component of public safety and merits review. Currently, BuChE is extracted from outdated human blood supplies, but it can also be made recombinantly in cell culture, transgenic animals, and plant systems. The second case study focuses on the cellulase complex, a mixture of 4–6 enzymes used to saccharify cellulosic feed stocks for the production of ethanol as a fuel extender. This target was selected for study because, for more than 30 years, the cost of cellulases has been a major impediment to the economic viability of cellulosic ethanol programs. Cellulases were also selected because they represent an extremely cost sensitive product class on which to conduct case studies. We reasoned that if plant-based manufacturing showed economic promise for this class, then the economically advantageous production of less cost-sensitive biotherapeutics and other products might also be anticipated. In contrast to BuChE, which consists of a purified molecule, the cellulase complex would be expressed in plants that are cultivated near the cellulosic feedstock and the bio-ethanol refinery and stored as silage without purification; the semidried catalyst biomass is mixed on demand with the cellulosic feed stock to initiate saccharification followed by fermentation. This approach varies significantly from previous approaches in which cellulase enzymes are produced via fermentation processes using native or engineered microorganisms.

For the cellulase case study, the plant-based cellulase production process is compared with a recent technoeconomic analysis of cellulase enzymes produced from Trichoderma reesei fer mentation using steam-exploded poplar as a nutrient source.The technoeconomic modeling for both case studies was performed using SuperPro Designer, Version 9.0 , a software tool for process simulation and flow sheet development that performs mass and energy balances,rolling bench equipment sizing, batch scheduling/debottlenecking, capital investment and operating cost analysis, and profitability analysis. This software has been used to estimate cost of goods in a variety of process industries including pharmaceuticals produced by fermentation and plant made pharmaceuticals. It is particularly useful at the early, conceptual plant design stage where detailed engineering designs are not available or warranted. Super Pro Designer was chosen because it has built-in process models and an equipment cost database for typical unit operations used in the biotechnology industry, such as bioreactors, tangential flow ultrafiltration and diafiltration, chromatog raphy, grinding/homogenization, and centrifugation. There are some unit operations and processes used in the case studies that are currently not included in SuperPro Designer, such as indoor or field plant cultivation, plant harvesting, vacuum agroinfiltration, and screw press/disintegrator. For the butyrylcholinesterase case study, SuperPro Designer’s “Generic Box” unit procedure was used to model these unit operations. For the cellulase case study, the indoor unit operations were modeled with the same software while the field production calculation and costs were tracked in Microsoft Excel spreadsheets. Unless otherwise noted, the costs of major equipment, unit operation-specific labor requirements and costs , pure components, stock mixtures, heat transfer agents, power and consumables used in the analyses were determined using the SuperPro Designer built-in equipment cost model and default databanks. For the cellulase case study, the program’s parameters such as water costs and total capital investment distributed cost factors were set to be the same as those used in the model described in Klein-Marcuschamer et al.; this SuperPro Designer model is also available at the Joint Bio-energy Institute technoeconomic analysis wiki site .

Additional case study specific design parameters were selected based on experimental data from journal articles, patent literature, the authors’ laboratory, interviews with scientists and technologists conducting the work cited, technical specification sheets or correlations, heuristics, or assumptions commonly used in the biotechnology and/or agricultural industry. The case study models were based on a new “greenfield” facility, operating in batch mode, although annual production costs neglecting the facility dependent costs were also determined to predict annual production costs using an existing facility. For the butyrylcholinesterase case study, annual operating time of 7920 hours for the facility was used with indoor grown Nicotiana benthamiana plants.For the cellulase case study, since the tobacco plants are grown in the field, it is assumed that plant growth occurs for 215 days of the year and the indoor facility is in operation for 127 days per year . For comparative purposes in the cellulase case study, the laboratory/QA/QC costs were neglected since they were neglected in the JBEI model and such costs are likely to be a minor component for the industrial enzyme case study.For the butyrylcholinesterase case study, the process flow sheet was split into separate modules to better understand the contributions of various process segments.Process flow and unit operations were derived from published methods and results from a number of sources as indicated in each case study, and from interviews with leading gene expression, agronomy, and manufacturing scientists and engineers who have participated in the development and scale-up of the processes described. On the basis of this information, the SuperPro Designer software was applied to calculate material inputs and outputs, bulk, and per-dose or per-unit costs.The two AI classes evaluated in these studies are produced in Nicotiana host plants. Nicotiana species, notably N. tabacum, N. excelciana, and N. benthamiana, are preferred hosts for PMB manufacture due to their metabolic versatility, permissive ness to the propagation of various viral replicons, and high expression yields achievable with a wide range of targets, as reviewed by Pogue et al., De Muynck et al., Thomas et al., Gleba et al., and others. Use of these hosts for production of clinical trial materials is also familiar to FDA and other regulatory agencies, thus facilitating Nicotiana’s acceptance in regulation-compliant manufacturing.

The enzyme is a globular, tetrameric serine esterase with a molecular mass of approximately 340 kDa and a plasma half-life of about 12 days; the plasma 1/2 is largely a function of correct sialylation. BuChE has several activities, including the ability to inactivate organophosphorus nerve agents before they can cause harm. With the recent use of chemical nerve agents such as sarin, there is continued interest on the part of many governments in stockpiling BuChE as a countermeasure. Currently BuChE is purified from outdated blood supplies; however, the high cost of this route and its low supply limit its utility. It has been estimated that extraction of BuChE from plasma to produce 1 kg of enzyme, which would yield small stockpile of 2,500 400- mg doses, might require extraction of the entire US blood supply.Large amounts of the enzyme are required for effective prophylaxis because of the 1 : 1 enzyme/substrate stoichiometry needed for protection against OP agents. Not surprisingly, recombinant routes have been explored and the enzyme can in fact be produced by microbial fermentation,grow table hydroponic animal cell culture, and transgenic goats and stably or transiently expressed in Nicotiana, albeit at modest levels of 20–200 mg/kg fresh weight biomass, with yield improvements being the target of ongoing research. The bacterial product is nonfunctional and the mammalian cell culture products do not have the plasma 1/2 needed for prophylaxis and may be difficult and expensive to scale, as discussed by Huang et al.. Goat milk produced BuChE can be obtained at 1–5 g/L milk, but consists mostly of dimers, is undersialylated and has short plasma 1/2. While expression yields are impressive, transgenic animal sources face challenges of herd expansion to satisfy emergency demand, as well as potential adventitious agent issues, and these challenges need further definition. Furthermore, of these options, only plant-based bio-synthesisyields an enzyme that is sialylated and appears to reproduce the correct tetrameric structure of the native human form in sufficient yield to be commercially attractive; hence, the plant-based route became the basis for our modeling exercise. Not surprisingly, the plant route for BuChE manufacture is also the subject of continued DARPA interest and support .BuChE can be produced sta bly in recombinant plants or transiently in nonrecombinant plants by viral replicons delivered by agrobacterial vectors introduced into the plants via vacuum-assisted infiltration. Relative to stable transgenic plants, the advantages of speed of prototyping, manufacturing flexibility, and ease of indoor scale-up are clearly differentiating features of transient systems and explain why this approach has been widely adopted in the manufacture of many PMP . In our analysis of BuChE, we used expression yields from several sources that evaluated various Agrobacterium mediated expression systems, including Icon Genetics’ mag nICON expression technology. Magnifection should be familiar to most readers of this volume as it has been applied in R&D programs throughout the world and its features have been the topic of multiple original studies and reviews ; therefore, the method is not described here in further detail. Likewise, the process of vacuum assisted infiltration has been described in detail by Klimyuk et al., Gleba et al., and others and is not further explained here.For BuChE, we mod eled the use of an N. benthamiana transgenic line modified to express the mammalian glycosylation pathway, beginning with a mutant host lacking the ability to posttranslationally add plant-specific pentoses but with the ability to add galactosyl and sialic acid residues to polypeptides, based on work recently reported by Schneider et al. .

Use of this host obviates the need to enzymatically modify the plant-made polypeptide in vitro after recovery to ensure the presence of correct mammalian glycan, a procedure that could substantially increase the cost of the AI. A glycan engineered host can be produced in two ways, by stable transformation or via use of multi-gene agrobacterial vectors. The feasibility of sialylation via the latter approach was shown recently by Schneider et al. for BuChE. Although there is an extra element of time required to develop a stable transgenic host compared to the transient modification of a pathway, the availability of a transgenic plant obviates the need to manufacture several Agrobacterium vectors carrying the genes for the product and two binary vectors carrying genes for the sialylation pathway; a procedure that would require additional capital and operational investments to generate multiple inocula in large scale. Therefore, for modeling upstream processes, we assumed that transgenic seed was available and that the resultant BuChE would have mammalian glycans and form tetrameric structures, and hence its biological activity and plasma half-life would be comparable to the native human enzyme.To model downstream purification of BuChE, we assumed harvest and extraction at 7 days after inoculation. Biomass disruption was by homogenization, followed by filtration and clarification, as generally described, but with modifications required for scale-up as indicated in Results and Discussion. Purification of the enzyme was by procainamide affinity chromatography. In the overall process, plant growth, inoculation, and product accumulation steps occur indoors in controlled environments, and extraction, clarification, and final purification of BuChE take place in classified suites, so that manufacturing and release of the enzyme can be compliant with FDA cGMP guidance for human therapeutics. Design premises for this process, specific assumptions used in modeling, and resultant cost calculations are presented .Cellulases currently under evaluation in bio-ethanol programs are all produced by microbial fermentation. Despite decades of research on lowering cellulase manufacturing costs, these enzymes still account for 20–40% of cellulosic ethanol production costs. Hence, lowering the cost of the biocatalyst is critical to the eventual adoption of bio-fuel processes that utilize renewable plant biomass feed stocks without competing with food or feed supplies. An alternative to fermentation produced cellulases is the production of these enzymes in crop plants, with the ultimate goal of producing cellulases at commodity agricultural prices. This process concept was modeled to estimate enzyme and ethanol costs produced by this approach. Should such a process for cellulases prove economically viable, it might encourage the production of other cost-sensitive PMB as well as bio-materials, food additives, and industrial reagents.Scale requirements and cost limitations of cellulases for bio-fuel applications constrained us to model production to open fields, with minimal indoor operations. We initially surveyed two scenarios for inducing production of cellulases in field-grown plants. The first was adaptation of the typical agroinfiltration method.

Further, most farmers strongly suggested the need for crop insurance that compensates in value terms, but they expressed no strong preference among compensations based on gross sales, profits, or production costs.Financial variables examined were off-farm incomes, gross sales, debts, and assets. Clearly, the portion of house hold income risk attributable to variation in farm income decreased as the share of off-farm income rose. For our sample, an average of 63 percent of income came from off-farm sources. A sizable segment of farmers, as many as 25 percent, derived less than 1 percent of their in come from farming in the year sampled. This is consistent with the observation that many of the farms were quite small, many farms operated at a loss in any given year, and there was a relatively large number of so-called “hobby” farms in California. Gross agricultural sales averaged about $0.4 million per farm for the entire sample. Vegetable farms averaged $1.1 million in sales, followed by ornamental crop farms with $0.8 million, and orchard farms with $0.3 million. About 6 percent of fruit/nut farms had sales of more than $1 million, compared to 29 percent for vegetable farms and 13 percent for ornamental farms. Agricultural sales were negatively correlated with off farm income share and positively correlated with acreage. Revenue per acre decreased as acreage increased. Given that specialty crops vary widely in unit value and in value per acre, this indicated that farms with fewer acres tended to grow crops with a high value per acre. Farms in our sample had an average of $1.4 million in assets and $0.6 million in debts. The average debt-to asset ratio was close to 0.5. This ratio is much higher than the 0.16 debt-to-asset ratio reported by the United States Department of Agriculture for all American agriculture in 2003. When viewing assets and debts as financial inputs necessary to generate revenue, the ratio of financial input to gross sales was highest for vegetables and lowest for orchard crops.This study provides a detailed statistical profile of an important segment of California agriculture, the horticultural crop industry.

The information provided is based on a unique survey of growers of horticultural crops, also known as specialty crops,vertical grow table that was conducted during the spring of 2002 at the request of the Risk Management Agency of the United States Department of Agriculture . This report presents data about horticultural industries in California and about the risk management attitudes, approaches, and needs of farmers producing these commodities. Specialty crops are diverse. These crops can best be defined by exclusion—as all agricultural crops excluding grain crops , oilseeds , cotton, peanuts, and tobacco. The bulk of specialty crops consist of fruits and nuts, vegetables, and ornamental crops . The industries featured in this study accounted for more than $16 billion of gross farm revenue in 2001. This value was more than 90 percent of the state’s total crop value and 60 percent of total agricultural value produced in California at the farm level. These industries are also important nationally. California accounts for 37 percent of the total value of horticultural crop production in the United States. In the past, these industries have expanded steadily in California, adding more than 300,000 acres between 1992 and 1997 . In the future, California’s horticultural industries are expected to continue to expand in size and importance. For the most part, horticultural growers have not been major recipients of farm program subsidies and have had relatively little government support compared to growers of commodities such as grains, oilseeds, cotton, sugar, and dairy products. Some horticultural crops have been eligible for USDA crop insurance programs and ad hoc disaster assistance, promotion assistance, and miscellaneous support, but the degree of subsidy has been small—typically around 5 percent of total value, compared to 30 to 50 percent and higher for grains, oilseeds, and cotton . Horticultural crops differ from other kinds of crops in their product characteristics, production processes, and market environments and thus in their risk characteris tics. The design of public policy for these crops must reflect management of their unique risks. Knowledge of market variables and grower risk behavior is essential to developing effective risk management tools for horticultural crops.

Unfortunately, while studies on traditional crops abound, little research has been done on horticultural crops. The objective of this survey was to generate wide-ranging statistical information that can be used broadly to better understand the horticultural crop industry, its sources of risk, and typical responses to those risks. The statistical profile of California’s horticultural producers presented here is the most exhaustive ever undertaken for this group. It draws on survey data collected from approximately one-third of all horticultural crop producers in the state. This report presents a large volume of information concisely. To do so, we summarize the methodology used to collect and tabulate the data; provide an over view of the seven topics addressed; and discuss the primary results. The discussion is organized by issue and includes a narrative describing the main findings for each topic. Selected figures and tables are included. The narrative is supplemented with a data section in the Appendix, which is organized into three parts. The first provides the response rate for each question in the survey. The second contains data tables organized by commodity category. The tables supplement the information presented in the narrative section with further disaggregated analysis. The last part of the Appendix provides the actual survey instrument.The first stage of the study, the survey of specialty crop growers, involved developing a questionnaire. The questionnaire was developed specifically for specialty crop growers based on the format of a survey instrument used previously , with input from RMA and from researchers who conducted an identical study in Florida, Pennsylvania, and New York. The California Agricultural Statistical Service assisted in formatting the questionnaire to facilitate its implementation. The final version of the survey instrument is presented in Appendix 3. We established the sample frame by defining a mini mum number of acres required for a farm to qualify for the study using information from CASS’s database. To be included in the study, a farm had to have at least five acres of perennial crops or at least two acres of annual specialty crops . This limit was designed to exclude very small farms that were unlikely to be commercial operations.

The acreage criterion was applied to CASS’s database, which contains information on more than 60,000 farms in California . A total of 31,864 farms met the acreage limit with the crops selected for the survey. CASS conducted two rounds of mailings and one round of telephone interviews to collect completed surveys. In total, the two survey mailings garnered 7,391 responses. Those mailings were followed by telephone interviews of growers who had not responded by mail, which collected an additional 7,746 responses. In total, 15,137 responses were received . Relatively few farmers answered all 25 survey questions, which required responses in 192 cells. Under some “usability” criteria on the completeness of the DATA COLLECTION AND AGGREGATION answers, some responses were discarded.1 In total, 10,410 observations were entered into an electronic database file that was then transferred to the authors. Our primary analysis used only the horticultural-crop based sample, mobile vertical grow tables which consisted of 10,200 observations.Among non crop categories, aquaculture producers provided the largest number of observations, allowing some statistical analysis of that industry. We provide data tables for aquaculture in Appendix 2 but omitted aquaculture from the narrative analysis. Note that sample size used in our analysis varies depending on the question being analyzed. Survey responses varied in degree of completeness, and valuable information could have been lost if only fully completed responses were used. Thus, to maintain the maxi mum sample size, different sub-samples were used, depending on the usability and appropriateness of the data provided, in analyzing particular issues. Information on sample size is included in most of the table presentations.Several mountain ranges in California create the dominant Central Valley and smaller coastal valleys where much of the state’s agricultural production is concentrated. The large Central Valley consists of the Sacramento Valley, which lies north of the San Francisco Bay Delta, and the San Joaquin Valley, which lies south of the delta. The Central Valley is encircled by the Cascade ranges and Klamath Mountains to the north, the Sierra Nevada Mountains to the east, the coastal ranges to the west, and the Tehachapi Mountains to the south. The coastal ranges also create a long strip of valleys, including, for example, Napa Valley and Salinas Valley. Climates in the region are affected by the cool cur rents of the Pacific Ocean and various mountain ranges. Temperatures in coastal regions are relatively mild while inland areas are hotter. Almost all of the state’s rain and snowfall occurs during late fall and winter . The majority of California’s water sup ply originates in the northern mountain regions of the state. Land for specialty crops is nearly all irrigated via ground water and various district, state, and federal water storage and distribution systems . California has 58 counties. In our analysis, we aggregated the counties into 11 regions with similar geographic and climatic characteristics as shown in Figure 1. The Sacramento Valley and San Joaquin Valley are together referred to as the Central Valley.California’s specialty crops include more than 200 individual crops.

To facilitate a manageable analysis, crop aggregation was needed. Crop codes were developed using three levels of classification. First, all the commodities were assigned to one of five basic categories: field crops, fruits and nuts, vegetables, ornamental crops, and non crop commodities. The last category included a small number of apiary and aquaculture farmers, but for category-specific analyses, we considered only aquaculture farmers because there were too few apiary farmers for any statistical analysis. Fruits/nuts, vegetables, and ornamentals, which were our focus, were then further divided into subcategories of similar types of crops . The third level of classification identified specific crops. Our data analysis used mostly the first two levels of classification. See Table 1 for a detailed description of the classifications. While classification of fruits and nuts into the second level is self-evident, such classification of vegetables needs discussion. A wide variety of vegetables appears in the data and choosing transparent and intuitive yet manageable groups was difficult. Following USDA guidelines, nine botanical classifications of vegetables were aggregated into six groups, guided by climatic growing conditions and by the number of observations available.Farm Size and Regional Profile discusses regional distributions of production for commodity categories and subcategories. It also provides mean acreage and acreage distributions. Mean acreages have relatively large standard deviations. To supplement this information, the distribution of farmers by acreage class has been included. Information provided on this topic pertains to Questions 1 through 6 . Crop Diversification provides information on patterns of crop diversification across crop categories and subcategories. For example, do farmers of perennial crops diversify into annual crops in the same way that annual crop farmers diversify into perennial crops, or do they tend to diversify within the same crop category? This section also includes information on organic farming. In formation provided in this section was obtained primarily from Questions 4 and 5 . Marketing issues include whether a crop is designated for processing or fresh use, the types of marketing channels used, and whether a farmer’s operation involves both growing and shipping or growing only. Marketing channels typically differ according to end use . Whether an operation grows and ships or only grows concerns crops intended for fresh use only; shipping and packaging are not issues for crops destined for processing, which are typically delivered to the plants in bulk. This section also explores the issue of whether price is predetermined through a contract before the time of sale. This section pertains to Questions 6, 7, and 8 in the survey. Yield, Price, and Profit Fluctuations for the preceding five-year period were explored next. Respondents were asked to provide actual yields for those five years; identify the highest fluctuation in yield, price, and profits during the same period; and indicate the main cause for their lowest profits.

When a garden can be surveyed in its entirety, visitors were more likely to consume it from afar than to indulge in its experiential qualities.Also implicit in the collective negotiated design process and the dynamic edge between the centre and external periphery of the garden was that gardens operate somehow as test-beds for operations at the landscape scale—in the same way as the pavilion is typically revered within architecture as an incubator for more expansive architectural praxis. However, the relationship of the garden to the landscape is far more dialectical than its architectural equivalent, and what goes in the garden is not necessarily an experiment for subsequent deployment in the landscape. The garden is more of a counterbalance than a small fragment of landscape; the two interact of course, but from a garden, a landscape does not necessarily grow. There are certainly exceptions to this rule—such as ‘seed dispersal’ concepts that were popular in the 1980’s where the garden was engineered to disseminate its genetic produce on the wind—but the point is that in these examples the garden is sacrificed to its expansion or duplication into the landscape Nevertheless, while not prefiguring landscape-scale operations, gardens have a more encompassing role as potent cultural litmus papers; as Bernard Lassus notes, ‘gardens have almost always foretold in advance the relationships between … society and nature’.In this regard, gardens are more persuasive as reflectors— either of self or society—than empirical experiments that generate results applicable to the world at large. This efficacy of the garden differentiates it from the landscape on the whole, although when we start to consider the consciously designed landscape as opposed to the general cultural landscape,plastic pots for seedlings the issue becomes more obfuscated.

My interpretation of James Corner’s characterization of the real limits to landscape architectural practice in the world illuminates this convergence. Given that landscape architecture influences only a very small percentage of outdoor construction projects, with other aesthetically unconscious operations undertaking the lion’s share, Corner positions landscape design as a primarily ‘metaphorical and ideological’ rather than solely demonstrative or performative praxis; one that uses its cultural currency to edify and illuminate an ecological message—to provide a foundation on which to reflect, rather than attempt to physically cure the world within its own diminutive footprint.This is, I would argue, is also descriptive of the role of the garden. Therefore, while a garden doesn’t necessarily equate to the landscape, the two genres increasingly converge and overlap in contemporary theory and praxis. At a conceptual level, the university gardens pertinently navigated the convergent muddy territory between gardens as reflectors and gardens as demonstrative landscapes. The move to de-frame is the key mechanism in engaging this terrain, although the one threshold that the design teams had no control over restrains its effectiveness: the fence around the Expo site itself. In this regard, the perimeter boundary is physical but also social; while the frame may enable representation by physically separating nature from the continuum of the world, division is also imposed through less tangible but equally powerful social forces. Indeed, to conflate the picturesque as an example, the ultimate frame was formed less from ha-ha’s or the limits of representation, than along lines of society and class. Beyond entrance gates and perimeter fences, garden shows are historically typically also be framed within these societal terms.Whereas William Kent may have ‘leaped the fence, and saw that all nature was a garden’, 66 to jump or destroy the wall of a horticultural expo is to typically find the periphery of a city, complete with its own implied social delineations.

It is in this context that the dissolution of the physical and psychological frame of the institutionalized expo itself— rather than the frames of the individual gardens within—that is the more potent force in contemporary landscape and urbanism.To provide the highest quantification accuracy when comparing samples one needs to minimize differences introduced in the processing of samples and acquiring the data. This can be best achieved through the introduction of stable isotopes into samples that allow samples to be mixed and then analyzed in the mass spectrometer. The application of metabolic labeling, which uses stable-isotope labeled amino acids in cell culture or 15N nitrogen-containing salts into the whole cell or organism in vivo, enables relative quantifications of proteins on a global scale. In such a quantitative experiment, one sample is labeled with the natural abundance , and the other with a stable isotope of low natural abundance during growth. The samples are mixed, processed, and analyzed by the mass spectrometer. Chemically identical peptides from these light- and heavy-labeled mixed samples co-elute by chromatography into the mass spectrometer, which can distinguish between the light and heavy peptides based on their mass difference, and thereby quantify the difference in peptide, and hence protein abundance between the samples. An alternative stable isotope-based strategy is to chemically tag peptides after enzymatic digestion; the most popular reagents for this strategy are isobaric tagging reagents Tandem Mass Tags . The TMT isobaric tagging reagents allow comparison of a larger number of samples, but the labeling is done at the peptide level after sample digestion and then samples are mixed. In contrast, the metabolic labeling is introduced into the proteins during growth, thus samples can be combined at the beginning, minimizing variations introduced by sample processing that can compromise quantification accuracy .

Although SILAC has been widely used in animal cell lines and has been the gold standard for MS-based proteomics quantification , 15N-labeling based quantitative applications are still quite limited in plants despite it being cheaper . This could be due to the complexity of the data analysis. SILAC pairs are easily identifiable because they have well-defined mass differences as typically only lysine and arginine are labeled. In contrast, in 15N labeling, each amino acid in the expressed proteins is labeled, and therefore, the mass difference in 15N pairs varies depending on the number of nitrogen atoms in their composition. Also, as more amino acids are being labeled, the effect of incomplete incorporation of the heavy isotope can be more pronounced under some conditions, such that isotope clusters of heavy labeled peptides in the survey scan MS1 spectra are generally broader, making it harder to identify the monoisotopic peak.There are very few freely available software tools with work flows that can analyze large-scale 15N labeled samples. Such tools include MSQuant , pFIND , and Protein Prospector . The workflow using MSQuant normally requires manual inspection of the pairs of the light and heavy forms that both fit with expected isotope envelope distribution; those that don’t fit the criteria will be omitted from further analysis . This makes it very time-consuming for a large dataset because of the manual inspection prerequisite. In addition,dutch buckets if both forms need to be present for quantification, then there will be a high false-negative rate for some of those highly biologically interesting proteins which only express in one of the two conditions, or from immuno precipitated samples where those proteins will be only in the bait-IP but may be completely absent in the control IP. Here, we present the 15N quantification workflow based on the free web-based software Protein Prospector . After data search with respective 14N and 15N search parameters, quantification between the light and heavy peptide pairs is done based on the identification of either the light or heavy peptide, or both.Additional features in Protein Prospector include a Cosine Similarity score which can be utilized to reduce manual checking of spectra and a cache function that enables efficient result retrieval through cached result storage. This workflow allows us to report quantifications of thousands of proteins and is applicable to the quantification of the total proteomes, sub-proteomes, and immunoprecipitated samples.This workflow can quantify thousands of proteins simultaneously. We demonstrate its performance using three in different proteins is relatively constant . With less complete labeling, the identification rate of heavy labeled peptides is significantly lower than light due to errors in monoisotopic peak assignment . If the labeling efficiency is achieved 98.5% or above, the identification rate between 14N and 15N search is similar in our experience. High-level labeling depends on three factors: 15N containing salt needs to be over 99% purity; we find 15N chemicals from Cambridge Isotope Laboratories are generally high-purity. The labeling time. We recommend growing Arabidopsis for 14 days to achieve high labeling efficiency. If plants can only be labeled for a shorter time before harvesting, then it is recommended to label the plants for one generation using a hydroponic system and start the experiment using the labeled seeds.

If the Arabidopsis plants are small after 14 days of growth, then the labeling efficiency will be lower, for instance, our acinus-2 pinin mutants are smaller than wild-type plants, therefore the labeling efficiency is lower than wild-type with the same duration of labeling. The availability of the 15N salt. Seeds should not be sown too many on solid-medium plates or in the liquid medium. We recommend the Arabidopsis plants are labeled 14 days or more to achieve high labeling efficiency and high identification rate, but users should be cautious not to stress plants by leaving them on medium for too long. Almost all proteins except seed storage proteins are labeled. These are not synthesized during the seedling stage and therefore they don’t incorporate the 15N labeling during growth and will remain unlabeled.Co-eluting peptides are common problems, especially in highly complex samples, and interfere with quantification. High resolution scans in MS1 reduce peak overlap, improving the accuracy of quantification , so we typically acquire our data at 120K resolution. High mass accuracy in MS2 helps to reduce the false discovery rate . Higher FDR was reported in the 15N sequence assignments due to more isobaric amino acid forms present in 15N labeling when the MS2 fragmentation was done using a low-resolution and mass accuracy QTOF2. To check this possibility in MS2 data acquired at high resolution,we compared the FDR in our seven labeled experiments listed in Table 2. After we combined peptides for 14N and 15N searches together with 1% FDR, we parsed the target and decoy 14N and 15N matches and calculated the FDR separately. We found the 15N data results had a lower FDR than that of 14N data search when MS2 scans were done in the high resolution and high-mass accuracy Orbitrap mass spectrometer . This trend is more pronounced in the higher labeling efficiency datasets. If FDR was calculated based only on first three datasets , there was no significant difference between 14N and 15N FDR, despite the average of FDR is slightly lower in 15N search. When four more Col/sec-5 datasets were included for comparison, the 15N FDR is significantly lower than 14N one, indicating using high-resolution and high-accuracy measurement, the unique mass of 15N modification to the amino acid may empower less random matches in data searches.After each peptide is quantified, they are compiled into protein groups in “Search Compare”. The spread of ratios for peptides from the same proteins are measured using the interquartile range, and Q1 , median, and Q3 are reported, as illustrated in Figures 5A,B and quantification of the pairs can be visualized as Figures 5C,D). Here we include two biological experiments as a demonstration. To calculate the median and Q1, Q3, the log base 10 of all the ratios of the peptides from the same protein are first calculated in Protein Prospector to generate log base 10 of median and Q1, Q3, followed by converting these log values to normal values by raising 10 to the power. To plot these quantification results, an R script is written as in Supplementary Data 1. In the R script, the log base 2 of all the ratios of the peptides are calculated and converted back to normal values by ratio 2 to the power. The plot is the same as displayed in Protein Prospector, no matter base 10 or 2 is used.A median value is preferentially reported instead of a mean value, as outliers, which are not unusual, can significantly skew the mean ratio, whereas median values are more tolerant. In general, the more peptides quantified from a single protein, the more accurate the median number is to the actual ratio.

For the coarse-textured soil, arsenic concentrations in sampled pinnae ranged up to 1890 mg/kg after 11 weeks and increased 2–3-fold after 21 weeks . Pinnae arsenic concentrations were con siderably lower for the medium-textured soil, never reaching the hyper accumulation threshold . The interaction of soil by time indicated that pinnae arsenic concentrations were lower at 21 weeks in ferns growing in the medium-textured soil com pared to coarse-textured soil. The mass of arsenic accumulated in sampled pinnae increased over time, increasing 4–5 times up to 1.1 mg at 21 weeks in the coarse-textured soil and 2–3 times up to 0.67 mg at 21 weeks in the medium-textured soil . At final harvest, soil type similarly affected fern frond arsenic concentrations and mass of accumulated arsenic per fern yet had the reverse effect on whole plant biomass . Fern arsenic concentrations in coarse-textured soil ferns ranged between 2666 and 3570 mg/kg for the whole plant, up to 10 times higher than the values in medium-textured soil ferns. The total mass of accumulated arsenic in coarse-textured soil ferns ranged from 15.2 to 20.2 mg/fern, about two times higher than in the medium textured soil . However, the fern dry biomass was 3–4 times higher in the medium-textured soil than in the coarse-textured soil, with values between 20.1 and 23.5 g for the whole plant . Soil treatment did not affect whole plant arsenic concentrations , mass of accumulated arsenic , or biomass . Arsenic concentrations were greater by up to 2 orders of magnitude in fern above ground biomass compared to the rhizome and roots . Mass of accumulated arsenic was greater by an order of magnitude in above ground biomass compared to rhizomes . Interactions of plant part biomass by soil and by treatment showed that senescent fronds were larger in the medium textured soil ferns compared to coarse-textured soil ferns, yet were smaller in phosphorus-treated ferns across both soils compared to in other treatments.

Within above ground biomass alone, arsenic concentrations were up to 8 times lower in mature and senescent fronds,hydroponic gutter compared to young fronds. However, total mass of accumulated arsenic was greater in senesced fronds , compared to young fronds across both soils. Here, the interaction of frond age and treatment indicated phosphorus-treated senesced fronds accumulated less total arsenic than young fronds. Whole plant phosphorus concentrations were 20% lower in ferns grown in the medium-textured soil , compared to in the coarse-textured soil . In contrast, mean iron concentrations were two to six times higher in ferns grown in the medium textured soil , compared to in the coarse textured soil . Phosphorus concentrations were higher in phosphorus-treated ferns .Across soils, soil , time , and depth affected pore water total arsenic concentrations . In the coarse textured soil, arsenic concentrations decreased after 3 to 7 weeks, with con centrations higher in the 27 cm depth than surface depths for the remainder of the experiments. In the medium-textured soil, pore water could be extracted from the phosphorus-treated columns till 17 weeks, longer than the control and F. mosseae-inoculated columns, where pore water extraction was not possible as early as 5 weeks into the study. Interactions of soil and time , soil and depth , and soil and treatment showed that in the medium-textured soil, pore water arsenic concentrations slightly increased with time, decreased with depth, and in creased with phosphorus treatment. Arsenic concentrations were very low in the coarse-textured soil pore water, less than 4.4 μg/L, but were higher in the medium-textured soil, with a mean of 13.6 μg/L increasing up to a peak of 109 μg/L in weeks 5 to 9 in the phosphorus treated columns . Concentrations of DOC were less than 32 mg/L in the coarse-textured soil pore water but higher in the medium-textured soil pore water, where they reached 165 mg/L . Depth affected pore water DOC concentrations. Interactions of soil by week and soil by depth showed that DOC concentrations increased with time and depth in the medium-textured soil but not coarse textured soil. Pore water iron concentrations were less than 66 μg/L in the coarse textured soil but higher in the medium-textured soil, up to 164 μg/L, and decreased with time .

A significant soil by depth interaction showed that iron concentrations decreased with depth in the medium-textured soil pore water. Phosphorus concentrations were less than 0.60 mg/L in the coarse textured soil pore water but were higher , up to 3 times those values, in the medium-textured soil pore water, and decreased with time in both soils . Phosphorus and total arsenic concentrations were moderately correlated . Soil , time , depth , and treatment affected pore water pH, which ranged from 6.0 to 8.9 in both soils and increased significantly with depth across both soils . Interactions of soil by time , by depth , and by treatment showed in the medium-textured soil that pH increased over time, decreased with depth, and increased with phosphorus treatment.Effluent elemental concentrations, volume, and cumulative leaching A soil by presence/absence of ferns interaction indicated that effluent arsenic concentrations were higher in the presence of ferns in the medium-textured soil , but that presence of ferns did not affect effluent arsenic concentrations in the coarse-textured soil . Across both soils, effluent arsenic concentrations increased with time . Effluent arsenic concentrations were lower in the medium-textured soil than in the coarse-textured soil . Phosphorus treatment lowered arsenic concentrations in effluent of both soils , regard less of whether ferns were present. Effluent volume and cumulative arsenic loss were greater in the absence of ferns, with up to 67 mL/day effluent leading to cumulative arsenic loss of up to 12.6 μg/day by leaching . Regardless of whether ferns were present, effluent volumes were greater in the coarse-textured soil where effluent flow lasted 22 weeks in the presence of ferns , leading to cumulative arsenic loss of up to 5.9 μg/day by leaching. This cumulative arsenic loss was more than from the medium-textured soil in the presence of ferns, where effluent flow ceased at 7 weeks with 50% less loss by leaching. Although in the presence of ferns effluent volumes were greater in phosphorus-treated columns , this did not lead to greater cumulative loss of arsenic from phosphorus-treated soil .

In the absence of ferns, cumulative arsenic lost from soil was lower in the phosphorus-treated soil .Bulk arsenic K-edge XANES spectra of the coarse-textured soil samples indicated greater abundance of arsenic in rhizosphere soil, compared to whole roots or bulk soil . In contrast,raspberry plant container in medium-textured soils, bulk spectroscopy showed rhizosphere soil arsenic fractions lesser than or equal to those in roots, with even lower abundance in bulk soil . In both soils, a similar or higher fraction of arsenic was found in phosphorus-treated soils compared to control samples . Micro-focused arsenic K-edge XANES spectra from coarse- and medium-textured soil showed that across all sample types, a higher fraction of arsenic was present in medium- than coarse-textured soil . In both textures we found very little evidence of arsenic reduction in aggregates from control soil . Compared to control aggregates, a higher fraction of arsenic was found in aggregates of phosphorus-treated soil in coarse- , Fig. 6C, Table SI-4 and medium- , Fig. SI-6C, Table SI-5 textured soil. Similarly, in medium-textured rhizo sphere soil, μXANES spectra showed a lower fraction of arsenic in control soils, but a higher fraction in phosphorus-treated soil . In coarse-textured soil, the fraction of arsenic on/within whole roots ranged up to 28.5% on control roots, 80.9% on F. mosseae-inoculated roots, and 20.0% on phosphorus-treated roots . In the medium-textured soil, the fraction of arsenic on/within whole roots ranged up to 99.8% on control roots, 106.0% on F. mosseae-inoculated roots, and at least 13.8% on phosphorus-treated roots , but good fits could not be obtained. In contrast, on particles adjacent to roots in medium textured soil the fraction of arsenic was only 18.2% in control soil and 3.5% in F. mosseae-inoculated soil . Bulk iron K-edge XANES spectra indicated iron oxyhydroxides were the most abundant species in coarse textured bulk soil, rhizo sphere soil, and roots . In medium-textured bulk soil, rhizosphere soil, and roots, iron oxyhydroxides were less abundant and were not present at all in phosphorus-fertilized roots . Other mineral groups identified through bulk and iron K-edge μXANES spectra in both coarse- and medium-textured soil included iron silicates, iron silicates, and iron silicates .The large increase in frond arsenic concentrations we observed with increasing soil particle size suggests changes in soil texture have a strong effect on arsenic phytoextraction rates, directly through arsenic phyto availability and/or indirectly through nutrient content and availability. Because arsenic strongly associates with the clay particle size fraction including iron oxides , arsenic phyto availability is lower in soils with higher clay contents . Our findings build on previous work showing P. vittata frond arsenic concentrations decrease as clay content in creases in medium to fine-textured soils and across wider clay content intervals . Even in the presence of apparently highly plant-available arsenic, P. vittata did not use the rhizome as a secondary storage organ, in contrast to previous observations . We showed that under high phytoavailability conditions, arsenic tolerance and hyper accumulation are simultaneous functional traits in P. vittata, if genetically independent . However, effective hyper accumulation—and/or tolerance— appears to exact a metabolic cost. We found lower biomass coupled with higher arsenic concentrations in ferns growing in the coarse textured soil, which suggests that at higher levels of phytoavailable arsenic , biomass decreases as resources are allocated to tolerance and hyper accumulation mechanisms.

In arsenic hyper accumulation, en ergy is used for active transport of arsenic via phosphate transporters, glutathione production, arsenic reduction, transport within xylem, and sequestration . The lower fern biomass could also be a response to the lower nutrient content in the coarse textured soil. Like arsenic, nutrient retention can be greater in soils with higher clay and organic matter contents . Extensive nutrient scavenging in the lower-nutrient coarse textured soil could expend metabolic energy, release arsenic from soil, and increase plant uptake of arsenic, requiring more resource allocation away from bio mass production toward sequestration.The greater fern arsenic accumulation coupled to greater loss of arsenic by leaching observed in the coarse- compared to the medium-textured soil suggests that plant-available arsenic is also available to leach. In the coarse textured soil, characterized by a lower iron content and adsorption capacity, arsenic appeared to leach from soil at all depths, not resorb to soil, and accumulate in pore water, leading to higher effluent arsenic concentrations. The peak in effluent arsenic concentrations in the coarse-textured soil suggests rapid, linear leaching of the most available arsenic fraction, similarly to what was observed in soils with 8% clay , followed by a decrease in concentrations as the most available arsenic fractions are depleted. Moreover, we attribute the greater effluent flow rates and duration in the coarse-textured soil to lower transpiration from the smaller above ground fern biomass. Lower biomass leads to lower transpiration, greater infiltration, and greater leaching of available arsenic, compared to the medium-textured soil which better supported plant growth. Yet even though the most leachable fraction was depleted early on from the coarse-textured soil, the highest fern arsenic concentrations were found in young fronds produced later in the study. This could suggest that arsenic continued to be plant available even after leaching decreased. Even in a soil with low adsorption capacity, the pools of arsenic available for leaching and plant uptake are overlapping but not identical.The lower arsenic leaching observed in the medium-textured soil is consistent with the greater clay and iron content and adsorption capacity, lower leachate volume, and more diffusive transport in this soil. Arsenic sorption and desorption processes appeared to occur at all depths, leading to constant pore water arsenic concentrations with depth, stable effluent arsenic concentrations lower than in the coarse-textured soil, and soil arsenic concentrations that increased with depth, indicating retention of arsenic re leased from the surface depth . Nonetheless, pore water and effluent concentrations in our study were still 4 to 40 times higher than in soils with similar or higher clay content , likely due to influent water pH and application rate simulating maximum daily rainfall conditions for an extended period.

The letter alleges that the new variety contains a piece of technology that in fringes upon a client’s IP claims. Furthermore, the patent owner appears not even to be interested in negotiating a license. And to this day, the legendary variety sits in storage somewhere in a greenhouse or a freezer, unused and sadly neglected. Of course, it is difficult to establish the definitive reasons why a project does not come to fruition, especially when there are numerous factors simultaneously affecting the outcome. Prior patents may be just a convenient excuse — and the patent owners a scapegoat — for tough decisions made to terminate unpromising or economically unattractive projects. Still, while patents do provide convincing incentives for private firms to invest in agricultural research and development , taking the necessary steps to respect the rights of patent ownership does add an additional layer of costs for developing new crop varieties. Economists call these additional costs “transaction costs”; they include legal fees for searching and filing patents and expenses for negotiating and drafting licenses. Royalties paid for using another’s technology are not IP transac tion costs. Rather, they are “rent” paid to use the technology and to compen sate for the R&D expenditures spent to create it. Commercial developers of agricul tural biotechnologies often take mea sures to avoid incurring these IP transaction costs. They may shift their R&D strategies or even acquire other companies to avoid dependence on outside technologies, thereby limiting expenses and preventing the complications and uncertainties inherent in “renting” them . These measures, however, can be costly too. Either way,square nursery pots costs faced under an IP system can, in theory, cancel out the private incentives created by IP to pursue innovation. More troubling, IP can even prevent publicly funded innovation from having its in tended social impact.

Yet are there any good indicators of this stalling beyond just stories and rumors? And if so, can we establish links with IP?Recent U.S. Department of Agriculture registrations for field trials of transgenic crops show that R&D in horticultural crops is lagging when compared with the major row crops. Even leading transgenic horticultural crops such as melon, lettuce, straw berry, grape, apple and sunflower are hardly represented in field trials . Horticultural crops are completely dwarfed by corn, the single most commonly tested transgenic crop, which by itself is the subject of almost half of all transgenic field trials. Of course, U.S. production of any single horticultural crop is far less valuable than U.S. production of corn. Less field-testing is to be expected for less valuable crops. But, even when applying a rough calculation to account for the differences in size and value of individual crops — dividing by the annual value of each crop’s U.S. production — horticultural crops tend to show a greater farm-gate value per field trial. In other words, horticultural crops are subject to fewer genetic field trials, and presumably receive less biotech R&D, for every dollar of crop production. Furthermore, the proportion of transgenic field trials conducted by public-sector research organizations, such as state universities or the USDA, versus the proportion conducted by commercial firms, varies widely by crop type . Public-sector involvement in the field-testing of the 10 leading transgenic crops — mostly major row crops — averages just 15%. Yet, in the next 20 mostly horticultural transgenic crops, public-sector involvement averages much higher, around 40%. These numbers should be interpreted cautiously, as the samples representing many of the horticultural crops are small and the ratios are taken over just a few field trials. For example, 16 field trials have been done on transgenic papaya and only 11 on transgenic walnut . Despite this variability, there appears to be less investment in biotech for horticultural crops than for major row crops, both in absolute terms and relative to overall crop values, while a greater proportion of that smaller R&D investment in horticultural crops comes from the public sector. Involvement by commercial firms in horticultural crops seems to be missing. While this data is too sketchy to conclude outright that commercial firms are under investing in horticultural biotechnology, it al lows us to ask whether they might be, and if so, why.

After a few early excursions into horticultural crops — most notably by Monsanto, As grow and Calgene as well as by Syngenta’s predecessors at Zeneca — major agricultural biotechnology firms have virtually shut down their product development in horticultural crops. Long-shelf-life tomatoes, virus-resistant squash and insect-resistant potatoes have not taken off as did Bt corn and herbicide-tolerant soybeans. Some of the specialized vegetable seed firms, such as PetoSeed , and some of the smaller agricultural biotechnology firms that specialized in vegetable crops, such as DNA Plant Technologies , continued their bio technology efforts a bit longer. Yet those efforts appear to have all but dried up in recent years. Instead, fruit and vegetable seed companies with active research and production activities, such as Seminis, Danson, Golden Valley, Harris Moran and others, continue to pursue their product development goals through conventional breeding techniques. One exception is the Scotts Company, which is currently seeking regulatory approval for a biotech product for golf courses, a glyphosate-resistant bentgrass. Indeed, most of the biotech work in horticultural varieties is conducted in university laboratories doing basic plant science. Occasionally, those projects spin out a commercially interesting trait or technology, but university technology-transfer offices have a hard time finding commercial partners among the seed firms, nurseries or growers’ associations.As with any investment, there is a degree of risk involved in putting re sources into the development of a new transgenic horticultural variety. Future returns are uncertain, and expected re turns are weighed against costs incurred to enter the marketplace. Such considerations also apply, more generally, to public-sector investments in re search. Although the measures of success may be more in terms of scientific advancements than earned profits, the practical importance of a new discovery is still important. .The size and strength of demand for a new transgenic variety will determine the size of returns on the investment. Market uncertainties for agricultural products are nothing new, due to such factors as disruptive competition in supply, cyclical price fluctuations and changes in consumer demand. How ever,ebb and flow tray some food consumers, such as in Europe, are skeptical of foods produced using biotechnology.

While a majority of U.S. consumers seem relatively unfazed by the genetic contents of processed bulk commodities such as soybeans and feed corn, consumers could react more strongly to obvious modifications of products in the produce aisle. Yet specific market uncertainties surrounding the use of transgenics could be addressed by the selection of technologies and traits that deliver real tangible benefits to consumers in ways that are perceived as unambiguously safe.The process of regulatory approvals for GM crops is essential to assure the safety of the technology. The R&D costs associated with gaining approval are considered up-front or “sunk” investments, and they must be spent to gain access to the market. These costs can be greater if the transgenic crop contains novel proteins or pest-control components, as additional assessments are required. In major row crops, investments to obtain regulatory approval can be recouped from the small technology fees charged on each bag of transgenic seed, which are multiplied out over millions of acres planted; however, with horticultural crops the distribution of regulatory costs is often concentrated onto much smaller markets. In many horticultural crops, several different varieties are commercially important. If introgression of the new trait via back crossing is not an option, such as may be the case for clonally propagated varieties that do not breed true, each variety must be separately transformed in the lab, and each must be separately tested and approved. Regulatory costs would add up, but they could not be spread out over nearly as large a market as they could for row crops. Still, returns per acre from horticultural varieties tend to be much higher, and the costs of specialized pesticides replaced by transgenic traits may also be higher. In addition, regulatory costs can be expected to decline as more risk assessments are completed, government agencies become more adept at judging the merits of different biotechnologies, and the policies and procedures become streamlined and finely tuned. In addition, the extension of an approach similar to the IR-4 program, which provides regulatory assistance for pesticides targeted to the needs of specialty crops , could reduce the regulatory burden on transgenic specialty crops.Transaction costs for gaining freedom to operate in the relevant IP protected technologies can be consider able. As with regulatory costs, the total IP transaction costs are independent of market size, and a larger number of transgenic varieties means more costly negotiations and more deals to cut. One industry estimate put the costs of negotiating a single crop genetics deal as high as $100,000.

When multiple patented genetic technologies are stacked in a cultivar, as is increasingly the case, the problem is compounded. Uncertainty over the total amount of IP transaction costs scares off investment in R&D projects, unless the expected returns are particularly attractive. This will continue as long as there is uncertainty in the IP landscape for plant bio-technologies and genetic materials. With the number of patents in this area growing at an exponential rate, IP access could be a deterrent to biotech R&D in horticultural varieties for years to come.IP access is a general problem for all of crop biotechnology. The reasons lie in the cumulative nature of the genetics and bio-technologies embodied in transgenic varieties. Plants are complex systems, and a healthy, productive crop plant has numerous genetic and metabolic pathways functioning together. Those genetics are inherited from breeding stock or can be added using biotechnology. A genetically engineered seed or plant cultivar may contain three different kinds of technological components that can be protected as IP, including the germplasm of the plant variety, the specific genes that confer a new trait and the fundamental tools of biotechnology such as genetic markers, promoters and transformation methods. The IP situation is complicated by a number of additional factors that add to the transaction costs.Different technological components of a transgenic crop variety are covered in the United States under different forms of IP law. If a variety is clonally propagated, the germplasm — the plant variety itself — can be claimed as IP at the U.S. Patent and Trademark Office under a Plant Patent, established in 1930 by the Plant Patent Act to protect against cuttings being taken, repropagated and directly resold under another name. Seed-propagated varieties can be claimed as a form of IP under the USDA system of Plant Variety Protection certification, established by the Plant Variety Protection Act in 1970. And, since 1980 — following a landmark decision by the Supreme Court in Diamond v. Chakrabarty over the patenting of a genetically engineered microorganism — all kinds of “invented organisms,” including novel plant germplasm, have come to be claimed as IP under standard U.S. utility patents. Subsequent technological and legal developments following Diamond v. Chakrabarty now allow utility patents to protect invented genes, proteins and other gene products, as well as biotechnology tools such as transformation of genetic contents, selection using genetic markers, and regulation of expression using genetic promoters. Finally, a significant part of the value of an agricultural variety often lies not in its technological or biological characteris tics perse but rather in its recognition and reputation among consumers in the marketplace. That “brand” name can be protected as IP by registering it as a trademark with the USPTO. The challenges posed by multiple layers of IP law are, if anything, greater for horticultural varieties than for row crops: plant patents, PVPs or utility patents may cover the germplasm; util ity patents typically cover the gene and biotechnology tools used; and trade marks are more often used to protect variety names. In leading row crops such as corn and soybeans, germplasm as well as the genes and bio-technologies are protected more consistently under only utility patents. While trade marks like Roundup Ready or Liberty Link refer to input traits and may be of some value in marketing to farmers, the identities of such agronomic traits command little notice or value from final food consumers.