Category Archives: Agriculture

Post structural theories like Actor-Network Theory move beyond the material to include the symbolic lives of commodities

Despite the extensive and growing literature on local and alternative food networks , this form of inquiry, which consists of “following the thing,” has not been extended to local commodities, including those produced through urban agriculture. Unlike global commodities, the products of urban agriculture are often equated with accountability and transparency and do not receive the same kind of critical scrutiny. We challenge this notion which conflates local with ethical by arguing that local food products, like global commodities, have complex symbolic and material lives that mask social relations. Their commodity circuits are shaped by socio-natural relationships involving people, places, things and forces that produce value both discursively and materially. This research builds on the commodity chain concept by implementing the sort of multi-locale ethnography employed by Cook to examine the local commodity circuits and micro-geographies of urban agriculture in San Diego County. In recent years, urban agriculture has seen a surge of interest in cities throughout the United States. This growing curiosity has been accompanied by increasing diversity in the networks of human and non-human actors enrolled in urban agriculture. For instance, the introduction of new production methods – namely, soilless hydroponic, aquaponic, and aeroponic growing – has increased the heterogeneity of urban agriculture networks in cities. This type of diversification, in particular, is the focus of this paper. Soilless and soil-based urban agriculture networks embody different, although sometimes overlapping, urban political economies and political ecologies . Further, the food commodities they produce are entangled in unique, locally articulated networks of human and non-human actors that materially and discursively shape the way food is planted, grown, harvested, marketed, desired, and consumed in the city. Inspired by Cook and Actor-Network Theory , we juxtapose vignettes from various nodes in the commodity circuits of soil-based and soilless urban agriculture products to better understand the place-based, socio-natural relationships that scaffold different urban agriculture commodities in San Diego County. Our contribution lies primarily in the comparative approach we adopt to study the networks underlying and shaping the activities of three urban growing sites in San Diego: Coastal Roots Farm, Solutions Farm,large plastic pots for plants and Mount Hope Community Garden, chosen based on their growing practices, discursive similarities and dissimilarities, and unique socio-spatial settings .

Rather than focusing on a single food item, such as a papaya, we consider the output of urban agriculture more broadly – whether it is a head of hydroponic lettuce or a radish pulled from the soil. Vignettes related to these three enterprises are the result of mixed method research that combines interview, media, US Census , and participant observation data. Thirty-four semi-structured interviews and participant observation were conducted between 2016 and 2018 at multiple sites in the local urban agriculture networks of the three case sites. The interviews were approximately an hour in length and covered institutional histories, actors’ personal motivations for participating in urban agriculture, their growing practices, their perceptions of the local food environment, and the struggles and barriers they perceive to urban agriculture. These data were analyzed using exploratory spatial data analysis , which allowed us to examine the socio-economic landscapes that are the setting for these actor-networks, and multi-locale ethnographic analysis, which included emergent coding in Dedoose online coding software . When coding the interviews, we paid particular attention to the race-, class-, and gender-based power dynamics that accompany different urban agriculture commodities as they travel from place to place gaining meaning and value. Combining and analyzing this data was necessary for examining the “people, connections, associations, and relationships across space” that influence justice narratives and practices. The comparative focus we take is a response to popular claims that soilless growing is incompatible with justice and calls for more reflexive, nuanced understandings of justice . The concept of local commodity circuits provides an innovative approach to analyze the power relations underlying various forms of urban agriculture and shaping their capacity to promote food justice. Finally, this research illustrates the practicality of a post-capitalist approach to justice that acknowledges incremental, but still important, steps towards building more just food systems in the absence of structural change. This theory builds on from the authors’ concept of “diverse economies” which recognizes “each individual economic transaction and practice as a possible site of struggle and ethical decision-making” and rejects a priori judgments that classify certain economic practices as “good or bad” . This position, we argue, provides a fruitful avenue for examining the placed, context-dependent justice practices that unfold in the “here and now” . Especially important is its ability to recognize everyday actions that can “support conditions for positive social and economic transformation” .

This weaves productively with the everyday, nuanced justice advocated by Goodman, Dupuis and Goodman in their reflexive theory of justice. Indeed, Chatterton and Pickerill note the need for “detailed empirical accounts of the messy, gritty and real everyday rhythms as activists envision, negotiate, build and enact life beyond the capitalist status quo in the everyday” . This research seeks to answer this call by examining the multiple openings for justice found throughout local urban agriculture commodity circuits. Commodity circuits are scaffolded by ‘geographical knowledges’– peoples’ understandings of specific places . These knowledges and/or imaginaries include the settings, biographies, and origins and are “fragmentary, multiple, contradictory, inconsistent and, often, downright hypocritical” . The concept of geographical imaginations builds on Marxism’s commodity fetishism, which recognizes commodities as more than physical – “they are both things and relations” that have social and geographic lives and trajectories that are hidden behind their exchange value .Here, commodities are hybrid actants, as much social as they are natural, that exist in networks held together by their relations . The idea of ‘actants’ is unique to Actor-Network Theory. Latour notes, “An actant can literally be anything provided it is granted to be the source of action” , recognizing the importance of things, which lack the motivations typically associated with human actors, in driving action . Agency, as result, is less about intentional actions, and more about associations or network . In this research, we focus on stakeholders and organizations and refer to them as ‘actors’ because they have motivations and particular agendas that drive their action. We do not intend to simplify or ignore the role of actants such as narratives, growing materials, permits, and more that “authorize, allow, afford, encourage,permit, suggest, influence, block, render possible, forbid, and so on” action . Agency is a “distributed effect” of the associations between these things and actors in Actor-Network Theory . Examining these associations “allows us to explain the mechanism of power and organization in society and to understand how different things … come to be, how they endure over time, or how they fail” . However, critics of Actor-Network Theory note that agency is not evenly distributed and that this question of power differentials is missing from the theory. In fact, “some actants ‘marshall’ the power of others and, in doing so,plant pots with drainage limit the latter’s agency” . This gap, we argue, is remedied by intersecting Actor-Network Theory with commodity circuit analysis in which power relations are a central characteristic of networks.

Geographies of food undoubtedly lend themselves to the use of Actor-Network Theory , although researchers have questioned the transformative potential of research that describing lived experiences and associations without explicitly engaging larger structures such as the political economy. Goss argues that this ‘cultural turn’ “risk[s] throwing out the babies with the bathwater: rejecting a caricature of commodity fetishism they lose a concept that provides insight into the relationship between the material and symbolic” . However, in response, Cook argues that the theory exists “between the lines” and exploring the everyday associations that underlie commodities does inspires empathy and political transformation . Despite their disagreement, the two vantage points have much to offer one another. We agree that if we, as researchers, are to be agents of change and inspire effective, political action, we must engage and embed audiences in the lives of ‘others’ to inspire empathy and challenge faulty geographical imaginaries. However, we must be more than story-tellers hoping that the pieces come together in the minds of our readers – we must use theory to articulate the connections that we hope audiences would find ‘between the lines’. This research seeks to do just that in its examination of local, urban agriculture commodity circuits. This research uses Actor-Network Theory to unravel the geographical imaginations that structure the people, places, things, and forces – the “dots” –in our networks. Seeing the dots as relational, hybrid, and situated allows us to untie anterior narratives around the socialness and/or naturalness of actants in our networks and focus instead on relations and connections as they relate to food justice. We do attempt to make sense of the connections for readers; however, we do not see this as creating a ‘critical knowledge’ for consumption as Cook and Crang have described it. Instead, we see it as handing our readers a map of the theoretical trails we have identified that they may follow or stray from as they examine and build their own understandings of these networks. This theoretical map is built from a series of vignettes presented side by side that allow readers to make connections and develop their own critical understandings as they “follow the thing” before we input our own critical understandings. This research does not end with these pages, but is a continuing collaborative effort between the actors and actants outlined in its vignettes, its readers, and ourselves. Cool, humid, bright. The greenhouse at Solutions Farms vibrates with slow, continuous activity.

Dave, a retired marine whose curiosity for the science of aquaponics led him to Solutions, reminds me not to take photographs of the workers – men and women from seemingly all walks of life – as they tend numerous rows of white, plastic trays overflowing with green and purple lettuces. The workers are participants in Solutions for Change’s program which seeks to break the cycle of homelessness in families throughout San Diego County. The program focuses on combining skills, knowledge, and resources to participants including “transformational” housing, health services, counseling, life skills like financial literacy, and job training. Get up, suit up, show up. The unofficial motto of the program stated by each team member I interview at Solutions Farms. Dots of red embellish the lettuces’ soft leaves like ornaments. Step closer and the dots come to life. Lady bugs crawling slowly across the leaves in search of aphids – small, pesky insects that feed on the lettuces’ sap and, ultimately, the farm’s profits. The fish – all male tilapia – live in 2,000-liter tanks in the aquaculture room next door. Warm, humid, dark. Dave conducts this orchestra of people, plants, fish, insects, fungus, bacteria, minerals, nutrients, moisture, and machinery. There’s more chemistry and biology and physics and engineering than you can shake a stick at 2 . He was a volunteer at the farm until their systems specialist put in his two weeks. An amalgam of people, places, objects, and forces shape and structure the local commodity circuits of soilless and soil-based urban agriculture described in the vignettes above. This research sought to connect the dots between these vignettes in order to “lift the veil” and uncover the social relations that underlie these often taken for granted circuits. We did so by combining commodity circuit analysis and Actor-Network Theory to examine and compare the socio-natural relationships that comprise the placed networks that structure the commodity circuits and influence their abilities to enact justice. This practice illustrates the nuanced nature of justice as it unfolds across urban agriculture commodity circuits and provides evidence of the relationships that create openings for justice to be enacted and/or co-opted by actors. In addition to examining the connections within and between the vignettes, we created a network diagram that encapsulates the people, places, and institutions enrolled in the separate urban agriculture actor-networks that span the three commodity circuits. The diagram illustrates the flows of knowledge, capital, labor, food, and other resources between actors.

The growing diversity of urban agriculture calls for research that accounts for its increasing complexity

The primary goal of this paper is to understand whether there is a connection between the growing practices organizations and businesses use and the themes present on websites, especially those associated with justice. This paper quantitatively grounds further discussion of the discursive realities of urban agriculture in the second paper, “Thinking and doing justice: urban agriculture in San Diego County.” Using three case studies chosen based on their online discursive representations , socio-spatial settings, and growing characteristics, I examine how local urban agriculture organizations, including soilless and soil-based, define and practice justice. This paper takes a reflexive approach to justice that moves away from “politics of perfection” and is embedded in spatial justice and a progressive sense of place that is “open and receptive to diversity and plurality” . Specifically, I assess the role of distribution, participation, and recognition in justice narratives and practices, paying special attention to the socio-spatial settings they are embedded in locally. Analysis centers around the role of land, labor, and capital—all of which are used in urban agriculture in various degrees and forms. Using a spatial perspective that acknowledges the importance of place and context, I explore the role of these three factors in producing opportunities and barriers for the three organizations to achieve justice, highlighting disparities in access, ownership, and management among them. Building on these case studies, the final paper, “Connecting the dots: local urban agriculture commodity circuits,” in collaboration with Dr. Pascale Joassart-Marcelli, use multi-locale ethnographic analysis to explore the complexities and nuances of justice across the three case sites’ entire commodity circuits. Here, we examine the complex symbolic and material lives of the urban agriculture commodities at these sites and the unique,square plant pots locally articulated networks of human and non-human actors that support them. These networks embody different, but often overlapping, urban political economies and political ecologies that materially and discursively shape food production, distribution, and consumption.

We juxtapose vignettes from various nodes along each case’s commodity circuit to understand the place-based socio-natural relationships, including those related to class and race, that scaffold urban agriculture commodities and invite readers to “connect the dots.” Together, the three papers present a thorough account of the idiosyncrasies of justice in the growing, and increasingly diverse, urban food movement in San Diego County. They acknowledge, but ultimately abandon divisive narratives that make a priori assumptions regarding the connection between growing method and justice and instead unravel the question of how different forms of urban agriculture contribute to justice. As will become clear in the coming chapters, justice is more complicated than an abstract concept or measurable outcome – it is a process that is constantly unfolding within and across space.Urban agriculture has a rich history in the United States, evolving from a 20th century strategy for self-sufficiency to a radical and alternative approach to food production in the 1960s and 70s . Today, urban agriculture is a highly-commoditized feature of the urban landscape and represents a growing sector of the green economy . It is also more diverse than ever – traditional, soil-based practices like community gardening and farming on vacant, urban lots are now accompanied by small-scale, technologically-advanced, soilless forms of food production like hydroponics and aquaponics that enable food to be grown on rooftops, in greenhouses and abandoned buildings, and in mobile shipping containers. These physical distinctions are also accompanied by interrelated variances in “scope, scale, type of access and for whom, participants, and goals” . For instance, the participants undoubtedly influence the narratives and goals of an urban agriculture project, whether it be environmental sustainability ; human health and well-being ; distributive justice and economic autonomy ; challenging historical legacies of privilege and marginalization ; and/or participation in the new food economy . Recently, researchers of urban agriculture have begun paying attention to actors’ motivations and the narratives underlying them . However, this literature focuses almost solely on actors operating in the traditional networks of urban agriculture practice , paying little attention to recent and innovative approaches to urban agriculture that incorporate technology.

This research provides an inclusive account of the narratives, specifically online web page content, of urban agriculture sites and organizations in San Diego County – a county with a rich agricultural tradition that possesses both soil-based and soilless forms of UA. We use a novel, computer-mediated method that reveals hidden trends and avoids unproductive researcher biases. The result is a map of discursive relationships that transcends what we call politics of technology in which the narratives, and ultimately goals and motivations, of urban agriculture sites are taken for granted based on their growing methods. This politics of technology, which classifies certain forms of growing as either ‘good’ or ‘bad’ based upon their use of technology, is misleading. Instead, we argue that there is nothing inherently good or bad about urban farming methods. To support this claim, in this chapter, I examine the motivations and goals that are highlighted in the narratives presented on the websites of San Diego’s main urban agriculture organizations. The primary focus here is the ways organizations represent themselves and their work to the general public, including volunteers, policy makers, and potential funders. In subsequent chapters, I will turn my attention to the practices of these organizations in an attempt to draw connections between discourses and on-the-ground activities. This means more inclusive research that recognizes the many forms of urban agriculture, including new soilless configurations. For the purpose of this research, we define soilless urban agriculture as urban food production in greenhouses and in/on buildings that use hydroponic, aquaponic, or aeroponic technology. This definition expands the idea of “ZFarming” – referring to farming on zero acres including “rooftop gardens, rooftop greenhouses, indoor farms, and other building-related forms” – by focusing less on the location of urban agriculture and more on the production process. It excludes vertical and rooftop farms that do not incorporate hydroponics, aquaponics, or aeroponics and avoids vague monikers like ‘innovative’ or ‘high-tech’ . The physical descriptors associated with soil-based and soilless urban agriculture differ in the literature .

Using the term ‘soilless’ allows us to untangle our classification from those already established in the urban agriculture literature and draw attention to actors, technologies, and spaces commonly missing in definitions of urban agriculture. Soilless urban agriculture is an emergent feature of the urban agriculture landscape throughout the Global North; however, it is still in an “early innovation phase” . Little scholarly literature exists on soilless urban agriculture save for a few examples on stakeholder perceptions , descriptions of practices and novelties , and assessments of environmental and economic impacts . What research does exist tends to conflate it with entrepreneurialism . Rooftop agriculture is gaining recognition for its community and social justice benefits ; however, growing food on rooftops represents only a small aspect of technological innovation in urban agriculture. Urban agriculture is also practiced in greenhouses, warehouses, and shipping containers with or without the use of soil. Further, soil-based rooftop gardens may not carry the same stigmatization as those that use soilless technologies. Recently, researchers have examined the contributions that aquaponics can make to urban food sovereignty in Milwaukee and Melbourne ; however, this type of research is largely lacking. Here, we attempt to correct the direction of the current research agenda. Just as the seminal critique by Born and Purcell challenged the politics of scale that privilege local food production as inherently better without critical inquiry into actors’ agendas, we challenge the politics of technology in urban agriculture that privilege certain production methods as ‘inherently better’ without examining actors’ narratives and practices. Researchers have examined politics of technology in the context of the design of information technology, exploring the construction of ontological differences between “technology” and “human work” . Latour has also grappled with ethical arguments around technology,plastic pots for planting arguing that it is how we engage with technology that tips the moral scales. We ultimately build on Born and Purcell , arguing that there is nothing inherently superior about any given urban growing process and confusing the means by which food is grown in the urban setting with the ends that growing food in cities aims to achieve is fallible. The use of advanced technology in urban agriculture requires a reflexive, critical examination regarding the diversity of participants, narratives, and practices in urban agriculture. This research is preceded by a growing body of literature that examines the motivations of actors involved in urban agriculture in cities throughout the Global North . Recent research on urban agriculture organizations and businesses throughout Canada and the United States provides an interesting national context, identifying a series of motivational frames based on survey responses including Entrepreneurial, Sustainable Development, Educational, Eco-Centric, DIY Secessionist, and Radical frames . This research reveals some interesting patterns, but unfortunately does not include technologically-advanced forms of growing. This investigation of motivations links productively to an analysis of the topics underlying urban agriculture narratives. Indeed, narratives around health, sustainability, justices, and more, often are driven by and drive motivations; however, as researchers note, examining advertised narratives and stated motivations is not a substitute for examining practices – see discussion of justice by Cadieux and Slocum . To that effect, this research is but a step in the process of understanding urban agriculture in San Diego County. Our research takes a different approach from its predecessors who have used both qualitative and mixed method research designs. Inspired by the ‘digital turn’ in Geography , we identify the narratives underlying urban agriculture using an innovative, computer-mediated quantitative method that combines natural language processing, dimensionality reduction, and data visualization.

This approach recognizes that “socio-techno-cultural” artefacts like website content create digital geographies linked to, but independent from, physical location. Here, Tobler’s first law of geography – “everything is related to everything else, but near things are more related than distant things” – is transposed to the digital world where all content produced by urban agriculture growers and organizations is related, but near things are more related discursively than distant things. We chose this approach for its ability to unveil hidden patterns in advertised content that may go unnoticed in other approaches such as surveys and interviews and avoid the politics of technology.The analytical methodology we pursue in this study relies on the delineation of ‘canonical knowledge structures’ representing common and generally accepted ideas about urban agriculture within the academic literature. To that end, we employed topic modelling, specifically latent Dirichlet allocation . This method is a popular choice for distilling themes from a collection of documents referred to as a corpus . A corpus may consist of any group of texts including peer-reviewed literature , grey literature, blog post , and social media posts like tweets . LDA identifies common word associations among the documents and performs statistical extraction of latent topics . In addition, a set of topic loadings is computed for each document . In effect, a “hidden structure” is thus inferred from the corpus by the algorithm. The granularity of the model, i.e. the number of topics, is a crucial consideration and input parameter, balancing model fit and interpretability . The topic model provides the top words and top phrases associated with each topic, which can be used to develop a descriptive label for each topic. To build our reference model, we first determined a source of “canonical” knowledge on urban agriculture. Suitable, recognized content on urban agriculture exists in many forms including scholarly literature, federal and state program information, planning documents, and nonprofit sector descriptions, among others. We chose to focus specifically on scholarly literature which gains canonical status through the peer-review and editorial process and represents the diversity of discourse around urban agriculture. Articles span diverse fields including ecology, geography, sociology, urban planning, chemistry, and engineering. Using the Web of Science database, we topic-searched journal articles containing noun phrases of ‘city’ and ‘urban’ in combination with the nouns ‘agriculture’ and ‘farm*1’ which returned 1,414 records including the article title, abstract, and keywords. We did not use a geographic criterion for our search. This search was performed on September 11, 2017. Still a relatively new subject in academic inquiry – the oldest item in the corpus dating back to 1959 – literature on urban agriculture has proliferated in recent years.

The field was organized in an RCBD with six blocks and four genotypes per block

The terminal 1 cm of the three seminal roots of each plant were collected at 6 and 16 DAG. Roots from 12 plants were pooled per replication to obtain sufficient RNA, and four pools were used as replications for each time point/ genotype combination. RNA samples were extracted using the Spectrum Plant Total RNA Kit . Messenger RNA was purified from total RNA using poly-T oligo attached magnetic beads. After fragmentation, the first-strand cDNA was synthesized using random hexamer primers, followed by the second strand cDNA synthesis using dTTP for a non-directional library. The library for transcriptome sequencing was ready after end repair, Atailing, adapter ligation, size selection, amplification, and purification. The library was checked with Qubit and real-time PCR for quantification and bioanalyzer for size distribution detection. The quantified libraries were pooled and sequenced on Illumina platforms. The clustering of the index-coded samples was performed according to the manufacturer’s instructions . After cluster generation, the library preparations were sequenced on an Illumina platform and paired-end reads were generated. The number of reads per sample and different quality and mapping statistics are described in source data of Fig. 6. Reads were mapped to the Chinese Spring Genome RefSeq v1.0 combined with the 1RS arm from cultivar Aikang58, allowing a maximum of 1 SNP. Reads were mapped using the splicing aware STAR aligner from the Lexogen pipeline. Reads mapping to more than one location were distributed equally among the identical targets. Expression values were calculated using the trimmed mean of M-values normalization method. The sequence of the 1RS.1BL translocation in AK58 is available only as a preprint and no final gene names have been published,round plastic pot so we provide a table with the different names and genome coordinates to facilitate future cross-reference.

Approximately 750 million tons of wheat are produced worldwide every year , but further increases are required to feed a growing human population. One understudied area that can contribute to these yield increases is the role of different root architectures on wheat adaptation to different soils. Although some progress has been made in the understanding of root development and architecture in Arabidopsis , this knowledge is lacking in grass species . There have been some examples of phenotypic selection of root architecture in breeding programs , but those methods are laborious and can be accelerated by a better understanding of the genes controlling wheat root architecture. Rye , a close relative of wheat, is more tolerant to water shortages than wheat, and has been reported to have a more robust root system. The translocation of the short arm of rye chromosome one to wheat chromosome 1B contributes to above ground biomass and better performance under drought stress . To address bread making quality problems associated with the 1RS.1BL translocation , a recombinant 1RS chromosome including two wheat 1BS chromosome segment introgressions was developed to eliminate the two rye regions associated with the bread-making quality problems . We introgressed the newly engineered chromosome into the spring wheat variety ‘Hahn’ and generated 1RS/1RSww near isogenic lines . Previous field trials showed that the Hahn 1RS lines had significantly higher yield and better canopy water status than the 1RSWW NILs in both well-watered and water-stressed environments, although the differences were larger in the latter . From a cross between Hahn-1RSWW and Hahn-1RS, we generated two additional NILs, one carrying the distal and the other the proximal wheat segment . The two NILs carrying the distal rye region showed significant improvements in grain yield and canopy water status compared to NILs carrying the distal wheat segment .

The 1RSxR NILs also showed higher carbon isotope discrimination and increased stomatal conductance, suggesting improved access to soil moisture relative to the 1RSxW NILs . In the winter of 2013, heavy rains waterlogged a UC Davis experimental field that affected the four 1RS NILs at the early tillering stage. Although the affected areas were irregular, the 1RSxR were less affected than the 1RSxW NILs. Based on this observation and previous results, we hypothesized that the 1RSxR lines might have a more extensive root system than the 1RSxW lines, which helped them tolerate both waterlogging in this experiment and water shortages in the previously published experiments . The first objective of this study was to characterize the effect of the wheat-rye polymorphism in the distal region of the 1RS.1BL translocation on root architecture in the field, and on plant biomass and grain yield under normal, excessive or reduced irrigation. After we observed that the lines with the distal wheat segment had shorter seminal roots than the lines with the distal rye segment in hydroponic conditions, we also decided to study the effect of these genotypes on seminal root growth rates, distribution of reactive oxygen species, and distribution of lateral roots. The implications of the observed differences in root development and architecture are discussed. In this study, we used four near isogenic lines that showed differences in grain yield in previous work . The recurrent common wheat parent of these NILs is the spring wheat cultivar ‘Hahn’ developed by the International Maize and Wheat Improvement Center . The Hahn cultivar carries the complete 1RS translocation from rye, and the three NILs differed from Hahn either in the presence of a distal interstitial segment of wheat chromatin , a proximal interstitial segment of wheat chromatin , or both . The interstitial wheat segments were introgressed from the common wheat cultivar ‘Pavon 76’ to eliminate the Sec-1 locus from 1RS and to incorporate the Glu-B3/Gli-B1 locus from 1BS into the 1RS chromosome to improve bread-making quality .

The source of this 1RS arm was the rye cultivar ‘Petkus’, and the resulting 1RS.1BL translocation became widely distributed in wheat breeding programs around the world . Controlled water logging experiments were conducted during the 2013-2014 and 2015-2016 growing seasons. An additional experiment was performed in 2014-2015 but it was not analyzed due to severe weed problems. The experiments were planted in November and harvested in June . The two water logging experiments were organized in a split-plot randomized complete block design with four blocks in 2014 and three blocks in 2016. Within each block, the main factor was irrigation treatment, and within each irrigation treatment – block combination, the Hahn 1RS, 1RSWW, 1RSRW, and 1RSWR genotypes were used as sub-plots. The average trait values of the 1RSxR and 1RSxW NILs were compared to determine the effect of the distal rye and wheat chromosome segments. In the 2014 field experiment, each block included two different irrigation regimes as main plots. The first treatment was based on plant needs and normal practices in California’s Sacramento Valley and is designated hereafter as normal irrigation. The second treatment, referred hereafter as water logging, consisted of artificial flooding twice a week starting in late January and ending in late March during the tillering stage, followed by normal irrigation. Water was applied via flood irrigation, and the soil profile remained saturated. While plants were not kept fully or partially submerged, there were persistent pools of water on the soil surface indicating a waterlogged environment. Each genotype was planted in three adjacent 1 m rows with 30.5 cm spacing between rows at a rate of 30 grains per row. Genotypes were separated by an empty row , and treatments were separated by a minimum of a border row, an irrigation levee, and another border row,round pot leaving in excess of three meters between experimental units of different treatments. Experimental units were replicated six times within each of the four blocks in an RCBD pattern and were used as sub-samples. At the end of the season, each set of three rows was harvested and grain yield was recorded. The average of the six sub-samples was used as a single data point in the statistical analysis. Canopy Spectral Reflectance measurements were taken for all sub-samples on two days . Sub-samples were averaged within days, and day averages were used as repeated measures. Canopy spectral reflectance measurements were taken with the “ASD HandHeld 2 Pro” spectrometer from Malvern Panalytical. Measurements were taken using a “scanning” method in which 50 measurements were taken on a single plot and averaged to give a single reflectance spectrum. From these measurements, differences in biomass between genotypes were estimated using the Normalized Difference Vegetation Index , which was calculated using the formula /, where R = reflectance at the specified wavelength. In the 2016 field experiment, each block included three irrigation treatments. The first treatment was grown under normal irrigation as described above.

The water logging treatment included flood irrigations three times a week, from the beginning of February to the end of February, followed by normal irrigation. The terminal drought treatment was grown under normal irrigation conditions until late March , and no additional irrigations after that point. Within each block–treatment combination, each genotype was machine sown in 2.23 m2 plots , which were combine-harvested at maturity. In 2016, CSR measurements were taken as described above on March 24th , April 6th , April 13th and April 28th . Days were used as repeated measurements and were analyzed as sub-sub-plots in an RCBD split-split-plot design using conservative degrees of freedom for days and all their interactions . After the CSR measurements were completed, an irrigation pipe ruptured flooding several sections of the experiment on April 29th, resulting in increased variability in the final yield measurements. Flooding was irregular and inconsistent across blocks, with major effects on replications two and three of the drought treatment and replication two of the waterlogging treatment. The field experiment to estimate root length was conducted after a maize crop harvested in the summer of 2016.Plots were machine sown in 4.5 m2 plots in November 2016 and were grown under normal irrigation conditions. To obtain soil core samples at specific depths and avoid differential soil compaction, we excavated ~2 m deep trenches cutting perpendicular across the middle of plots including complete blocks one , three and six to expose the root system. We took horizontal soil core samples from the center of each block at 20 cm intervals using a thin-walled copper pipe . Core samples were taken from 20 to 140 cm in the first block and from 20 to 180 cm in blocks three and six after we discovered the presence of roots at 140 cm in block 1. Plants were at the tillering stage at the time of the root sampling.Soil core samples were washed using a hydro-pneumatic elutriation system from Gillison’s Variety Fabrications, Inc. . After washing and sorting white turgid roots from other organic matter and decayed roots of the previous maize crop , we suspended the roots in water and scanned them using an EPSON Expression 11000XL flatbed scanner. Scanned root images were analyzed using the WinRhizo software package. Measurements of dry root biomass are not reported because they were too variable due to small biomass, stray soil contaminants, and changes in ambient moisture. The 20 cm sampling point was not used because the large amount of root biomass and organic matter present in these samples made them difficult to clean and measure. Since all root measurements were performed using soil cores of identical volume we refer to these measures as densities . Differences in total root length, surface and volume density, average root diameter, and root tips and fork densities were analyzed using a split-plot design with genotypes as main plots and depth as subplot. This is a conservative statistical analysis because it reduces the df for genotype from 3 to 1. Therefore, we also compared the two same pairs of genotypes using statistical contrasts in an ANOVA including all four genotypes. To account for the inability to randomize depths, we used a conservative estimate of the df for subplots and for the interaction between subplot and main plot. Conservative df were calculated by dividing their df by the number of subplots. This strategy is similar to that used for repeated measures in time and does not affect comparisons among main plots , which are the main objective of this study. Homogeneity of variance and normality of the residuals was confirmed for all the individual ANOVAs performed at each depth for all parameters.

A change in this ratio from the control suggests a change in the overall health of a plant

At the end of the 7 d incubation, root growth of lettuce seedlings was found to increase with increasing rates of the CEC mixture with significant differences observed at the 2X, 10X, and 20X concentration . Compared to the control, root length was found to increase by 16 ± 3, 24 ± 6, and 32 ± 8 % at the 2X, 10X, and 20X CEC concentration levels, respectively. This was in contrast with studies that showed negative root length effects when plants were exposed to other CECs such as tetracyclines and sulfonamides . However, in those studies, high concentrations of a single CEC were generally considered. For example, Liu et al. observed inhibition of root growth in oats, rice, and cucumbers when the seedlings were exposed to oxytetracycline concentrations at 5-10 mg L-1 . Chemical mixtures may involve more complex interactions, where various chemicals may have different but related targets that can have an additive or nonadditive effect . This may be the reason for the observed stimulatory effect by the CEC mixtures at environmentally relevant concentrations in this study. It could also be the result of a biphasic response where a favorable biological response at low dose and inhibition at high dose is observed, a phenomenon known as hormesis . Primary root length after 7 d germination is indicative of the plant’s ability to establish itself and obtain nutrients during this critical period of development. The stimulatory effect on root length observed in response to the low-dose exposure of a mixture of CECs in this study suggested that a low-dose mixture may help the plant establish itself better and increase its ability to obtain water and nutrients during the beginning stages of growth. However,10 liter drainage collection pot it must be noted that only a small set of CECs were considered in this study, and a similar response may not necessarily occur for other CECs or for these CECs with a different species.

Roots, stems, and leaves each maintains their own dynamic balance in biomass that is indicative of the relative above-ground resources and below-ground resources . The root to shoot biomass ratio provides insight into the overall health of the plant. A lower root to shoot ratio suggests greater investment in above-ground tissues possibly due to interference with photosynthetic mechanisms or interference in root functioning, resulting in reduced nutrient uptake and therefore growth . A greater root to shoot ratio is typically influenced by below ground conditions, suggesting reduced water and nutrient availability. Although no significant differences in root to shoot ratio with respect to biomass during the 7 d study, a positive correlation between CEC treatment levels and root to shoot ratio was observed , suggesting a possible interference with nutrient or water uptake by the roots. This was in agreement with Carter et al. , who found that carbamazepine and verapamil exposure caused changes in sodium and calcium ion flow regulation in zucchini plants, demonstrating the influence of CECs on nutrient transport. Since toxicity can only be elicited when a chemical has reached its target site, we monitored bio-accumulation of the target CECs into various cucumber tissues. The starting concentrations and their dissipation in the nutrient solution after 3 d with and without plants are found in Table 6. The 20X CEC treatment was used because the higher concentrations facilitated qualitative evaluation of CEC bio-accumulation and translocation. Among the various cucumber tissues, only one flower sample per treatment was collected due to the limited growth duration and plant tissue. Samples of flowers had to be pooled from replicates for each treatment, and therefore some standard deviations could not be calculated for the CEC concentrations in flower samples. Concentrations of CECs in plant tissues increased with increasing concentrations in the hydroponic solution . All CECs except triclosan were detected in the roots .

The absence of triclosan in the root samples could be due to its relatively high quantification limit of triclosan , active metabolism , or suppressed uptake of triclosan in the presence of other CECs. Above-ground and below-ground biomass were measured for cucumber plants at the end of a longer-term exposure to the same CEC mixture in hydroponic solution at incremental levels. Biomass measurements are useful in measuring stress response, as deviations in growth from the control are indicative of the overall sum of response of the plant . Although there were no significant differences in the biomass among the different CEC levels, there appears to be a dose dependent response when change in biomass, expressed as the percentage difference relative to the control, was considered . At the 20X treatment, the relative percentage differences in the average below ground, above ground, and total biomass from the control were -51.2 ± 20.9, -26.3 ± 34.1, and -33.2 ± 41.7%, respectively . The greatest reduction in plant biomass occurred in the roots, and this finding was similar to Carter et al. who also observed a ~30% reduction in the below ground plant tissues of zucchini from the control when the plant was exposed to 10 mg kg-1 carbamazepine in soil. The observed reduction in above-ground biomass and total biomass along the dose-response curve suggested that there was not simply further investment in photosynthetic or aerial tissues due to interferences in photosynthetic mechanisms, but rather that multiple aspects of the plant were affected without ways to mitigate the stress . It was also possible that the roots could not support an increase in aerial tissues, the common stress mitigation mechanism, because the roots were also under stress and were unable to take up the necessary nutrients to promote growth.A hormone profile was analyzed to further understand the dose-response effect of chronic exposure to a mixture of CECs on cucumber plants . In this study, we focused on three phytohormones; auxin , jasmonic acid , and abscisic acid because of their critical roles in regulation of a plant’s development and stress-response. The auxin profile was characterized by a hormesis effect along the dose-response curve when the leaves and stems were considered . The solvent control did appear to have some stimulatory effect on auxin concentrations in the stems , but the change was not statistically significant . A 6-fold increase was observed in the stem auxin concentrations at the 1X CEC treatment level as compared to the control .

The trend, however, was followed by a gradual decrease to 2-fold the control at the 10X CEC treatment rate . The leaf auxin concentrations significantly increased at the 1X and 10X CEC treatment rates to 16 and 11-fold, respectively,10 liter drainage pot which was followed by a decrease at the 20X CEC treatment rate. A similar pattern in leaf auxin content was also observed by Carter et al. along a dose-response treatment of carbamazepine for zucchinis grown in soil. A similar pattern, however, was not visible for the auxin content in the roots or fruits at the end of 30 d cultivation in this study. Auxin is known to be involved in cell elongation and division of meristematic tissues. The observed increase of auxin inthe stems and leaves at CEC levels as low as the 1X treatment rate suggested that the stems and leaves were being signaled to grow in order to gain increased light exposure because of interferences with photosynthetic mechanisms, and/or decrease heat stress by allowing for more air flow. Jasmonates are phytohormones that are involved in flower development, fruiting, reproduction, and plant defense. No clear trends or significant differences were observed in JA levels in any of the plant tissues along the dose-response curve . This could be due to the time of sampling, as the plant was still in an early stage of development , when flowering and fruiting was not the primary focus of the plant. Instead, at this point in development, increasing photosynthetic tissues was likely of the upmost importance. ABA is a signaling hormone that communicates water stress to the plant. ABA levels were significantly elevated in the leaves with exposure to increasing levels of CECs and significantly decreased in the roots at environmentally relevant concentrations of the CEC mixture . ABA in the roots dropped from 56.5 ± 17.3 ng g-1 in the controls to 8.23= ± 9.5, 5.6 ± 2.2, and 11.8 ± 13.7 ng g-1 at the 1X, 10X, and 20X CEC treatment rates. Low ABA levels in the roots could indicate over-saturation by water at the root tips. In this study, we observed an approximate 20% decrease in root ABA levels when the plant was exposed to the CEC mixture at the 1X level as compared to the control, demonstrating that even exposure to CECs at low levels could significantly affect the homeostasis of this hormone. The decrease in the ABA levels coincided with visual symptoms of the roots, where the roots appeared to be over-saturated and less rigid structurally, which also resulted in a ‘shedding’ of some small roots into the hydroponic medium. In the leaves, ABA was found to increase significantly at the 1X, 10X, and 20X CEC treatment levels from the control 42.6 ± 12.8 ng g-1 . Elevated ABA levels can cause stomatal closure, thereby reducing transpiration in a plant’s efforts to conserve water . The increase of ABA in the leaves and its resulting effect on anti-transpiration and therefore decreased pulling force of nutrients to aerial tissues could be the reason for the reduction in above-ground biomass observed in this study. Antitranspiration activity may also impose an impediment on plant growth by limiting gas exchange and impairing the plant’s ability to adapt to additional stressors such as extreme temperatures . With stomatal closure, the plant’s ability to mitigate heat stress by transpiring is also impacted, threatening its survival. 2.3.5. Phytohormone response to multiple stressorsFollowing cultivation in CEC-containing nutrient solution, a subset of cucumber plants was exposed for 4 d to heat stress at temperatures up to 41 °C in a greenhouse, and the plants were then sampled for hormone analysis.

JA content was not significantly altered with the additional heat stress in the roots and stems . Although, a significant effect on the JA content in the leaves was not observed following any of the lower level CEC treatments, JA content in the 20X treatment was significantly increased from JA content in plants exposed to heat without CEC exposure . A consistent trend across CEC treatments was a decrease in the JA content in the leaves in response to heat stress.Jasmonates are important signaling molecules in plant defense, and therefore a decrease in JA content in leaves in response to heat stress across all CEC treatments has implications for plant survival when exposed to disease, wounding, or pathogens . Although heat-stress exposed plants did not have statistically significant changes in JA content, this decreased trend in the JA content in leaves exposed to excessive heat conflicts with a study where heat shock was found to result in an upregulation of JA pathway genes and its consequentially enhanced production in agarwood cells . This could be due to the type of heat exposure , the range of temperature exposure, or the difference at the cellular level . Auxin concentrations in the roots of the control treatments with heat stress were significantly elevated as compared to the 1X and 20X CEC treatments . This finding showed how different types of stress may have opposing effects on plant hormone levels. In the stems, heat stress resulted in a significant decrease in auxin concentrations in plants in the 1X CEC treatment as compared to the 1X CEC treatment without heat stress , however the 1X CEC treatment with the added heat stress was not statistically different from the control or the 20X CEC treatment. The role of auxins in cell division and elongation has recently been associated with being an adaptive growth response to high temperature tolerance as seedlings elongate to elevate photosynthetic and meristematic tissues away from the heat-absorbing soil, thereby allowing increased air circulation and cooling effects . Leaf auxin concentrations were not affected by heat stress . Between the control and 20X CEC treatments, heat stressed plants displayed only slightly elevated auxin contents from their respective CEC treatments without the additional heat exposure. ABA is integral to how plants mitigate heat stress.

Individual kernel mass was greatest under both ambient and elevated CO2 treatments

The germination paper was placed in a 400 mL beaker with approximately 75 mL of 10 mM CaSO4 solution, covered with a plastic bag and placed in an incubator for four days. Seedlings were transplanted into 20 L tubs filled with an aerated nutrient solution that contained 1 mM CaSO4, 1 mM K2HPO4, 1 mM KH2PO4, 2 mM MgSO4, and 0.2 g L−1 Fe-NaEDTA and micro-nutrients 2HPO4 as the N source, Epstein and Bloom, 2005. The nutrient solution was replaced weekly and an additional 0.2 mM of NO− 3 – or NH4 + − N was added midweek until harvest. The solution volume was maintained by daily addition of deionized water. Solution pH varied between 6.8 and 7.0 for both of the N forms, and the NH4 + and the NO− 3 solutions did not differ by more than 0.1 pH units. The plants were grown in controlled environment chambers set at 23/20˚C day/night at 60–70% relative humidity with a photo period of 15 h. The photosynthetic flux density was 375µmol m−2 s −1 at plant height. Plants were subjected to one of three CO2 concentrations: “sub-ambient” , “ambient” , and “elevated” . sub-ambient CO2 concentrations were maintained by passing air that entered the growth chamber through wet soda lime, a mixture of KOH, NaOH, and Ca2 that was replaced as needed. The elevated CO2 conditions were maintained in an environmental chamber equipped with non-dispersive infrared analyzers for CO2 and valves that added pure CO2 to the incoming air stream to hold the chamber concentration at 720 ppm. The wheat was grown until all above ground parts turned completely yellow. Plant matter was sorted into grain, chaff, shoots,growing strawberries vertically and roots and dried for 48 h at 55˚C. Data on kernel number , kernel mass, number of heads, kernels head−1 , and HI were collected prior to sample preparation for nutrient analysis.

A portion of the grain was analyzed for phytate using a modification of the method as described by Haug and Lantzsch . The remainder of the grain as well as the shoots and chaff was bulked into five repetitions per treatment and sent to the UC Davis Analytical Laboratory for nutrient analysis. The roots of plants for each CO2 × N treatment became entangled within the same tub; therefore, we were unable to separate the roots of the individual plants for analysis. Root data are thus presented as means for each treatment with no standard errors or confidence intervals. Data were analyzed using PROC MIXED . Nitrogen form and CO2 factors were treated as fixed independent variables. We used the Tukey–Kramer Honestly Significant Difference test for mean separation. Probabilities less than 0.05 were considered significant. Because some of the transformed variables did not meet the assumption of homogeneityof variances, but one-way ANOVAs met the ANOVA assumptions, we analyzed the results via one-way ANOVAs to gain some information on the interactions between CO2 and N form.We used a database derived from the United Nation’s Food and Agriculture Organization ’s national food balance sheets to estimate the average daily per capita dietary intake of zinc and phytate from 95 different food commodities in each of 176 countries. This database combines FAO data on per capita intake of food commodities with USDA data on the nutrient or phytate content of each of these commodities. More detailed discussion of the creation of this database for the International Zinc Collaborative Group may be found in Wuehler et al. . Using this database, we produced two datasheets: one containing per capita daily dietary intake of zinc from each food commodity for each country and another containing per capita phytate intake from each food commodity for each country. To calculate total dietary zinc and total dietary phytate per country, we summed across the rows of all food commodities for each respective country. To determine the proportion of a population at risk for zinc deficiency from a hypothetical least developed country , we first calculated TDP and TDZ values for a set of 44 countries defined by the United Nations as being least developed. We took the mean TDP and TDZ values for these countries to represent a hypothetical “less developed country.” To calculate the bio-available zinc portion we used the Miller equation .

Mean TDZ and TDP values were converted to mg mmol−1 and put into the Miller equation to compute the average per capita TAZ in our hypothetical LDC. The variables TDZ, TDP, and TAZ are described above, and Amax, KP, and KR are constants as described in Miller et al. . We made an assumption that our hypothetical LDC receives half of its phytate and half of its zinc from wheat, which is roughly consistent with many of the LDCs in the FAO database. We analyzed the effect of elevated carbon dioxide levels on TDP, TDZ, and TAZ concentrations in a hypothetical LDC population for both NH4 + and NO− 3 -supplied wheat. To calculate a new TAZ for wheat grown under elevated CO2 conditions, we first calculated the percent change in TAZ from ambient to elevated levels for wheat receiving NH4 + or NO− 3 . This computed percent change was then applied to half of the hypothetical TDZ and TDP; meanwhile, the other half of the hypothetical TDZ and TDP remained unmodified. Thus, the total new TDP and TDZ is the sum of the unmodified and modified portions. These new TDP and TDZ values for both NH4 + and NO− 3 -supplied wheat were then put into the Miller equation to compute new hypothetical TAZ values for an LDC. Differences and corresponding percent changes between the new TAZ values and the original TAZ value for a LDC were computed to determine the overall affect of elevated CO2 on TAZ in NH4 + and NO− 3 -supplied wheat for an average developing world population. TAZ, TDP, and TDZ concentrations can only be compared within a single N form across the CO2 concentrations due to methodological constraints of the model. Plants supplied NH4 + vs. NO− 3 nutrition reacted differently to CO2 enrichment . Plants supplied NH4 + differed across CO2 treatments for most of the yield and biomass measurements. The greatest values typically were found at ambient CO2 concentrations. Shoot, chaff, grain yield, number of heads, and KN were greatest at ambient CO2 levels. HI and kernels head−1 showed no change across CO2 treatments. In contrast, biomass and yield measures of NO− 3 -supplied plants did not differ among the three CO2 concentrations.

At sub-ambient CO2, differences between the NH4 + and NO− 3 treatments occurred in shoot biomass and three of the yield components: kernel mass, head number, and kernels head−1 . Ammonium-supplied plants had a larger number of heads while NO− 3 -supplied plants had greater shoot biomass, kernel mass, and kernels head−1 . At ambient CO2, NH4 + -supplied plants had a greater number of heads and greater chaff biomass. Plants supplied NO− 3 had a larger number of kernels head−1 . At elevated CO2, biomass and yield measures did not differ with N treatment. Phytate was relatively insensitive to CO2 concentration. Phytate concentrations were highest at sub-ambient CO2 for NH4 + -supplied plants . Sub-ambient CO2 also produced the lowest phytate concentrations in NO− 3 -supplied plants. NH4 + -supplied plants had greater phytate concentrations than NO− 3 -supplied plants at sub-ambient CO2,best vertical garden system but not at the other CO2 concentrations. Grain from plants grown under NH4 + nutrition had roughly 7, 18, and 8% higher bio-available Zn than NO− 3 -supplied plants at sub-ambient, ambient, and elevated CO2, respectively . Based on this phytate and bio-available Zn data, we modeled how a human population from a LDC would be affected by changes in atmospheric CO2 concentrations . The calculations were based on differences among CO2 concentrations; therefore, modeled TDZ, TDP, and TAZ values cannot be compared between NH4 + and NO− 3 -supplied grain. Grain from plants supplied the different N forms behaved differently as CO2 concentration increased. We found that under NH4 + supply, TAZ would increase 3.6% with the rise in CO2 from sub-ambient to ambient, and decrease 1.6% with the rise from ambient to elevated CO2 . Humans provided NO− 3 -supplied wheat would experience a decrease in TAZ of 3.5% going from sub-ambient to ambient, and an increase 5.6% from ambient to elevated CO2 . Ammonium-supplied plants generally showed a trend toward decreasing nutrient concentrations with increasing CO2 concentration while NO− 3 -supplied plants varied widely across CO2 treatments . The decrease in nutrient concentrations under NH4 + supply corresponded to an increase in root mass. Nitrate supplied plants tended to have their highest nutrient concentrations in the ambient and elevated CO2 treatments. Ammonium supplied plants had higher concentrations of Zn and Mn across all of the CO2 treatments, as well as higher total N and Fe at sub-ambient CO2. Nitrate-supplied plants typically had higher concentrations of the other nutrients at all CO2 concentrations.

The distribution of nutrients and micro-nutrients among plant parts followed similar patterns in both the NH4 + and NO− 3 – supplied plants, although the NH4 + -supplied plant distributions were slightly more variable . Allocations to root and grain usually were greatest at ambient CO2, and those to chaff and shoots at either sub-ambient or elevated CO2. Grain typically contained the largest proportion of total N, P, Zn, and Cu, although the organ with the largest percentage of Cu varied with CO2 treatment among NO− 3 -supplied plants. Plants at sub-ambient and elevated CO2 allocated more Cu to the grain, while those at ambient CO2 allocated more to the roots. In general shoots received the majority of K, S, B,Ca, and Mg for all N and CO2 treatments. Ammonium-supplied plants allocated slightly more Mn to the roots at sub-ambient CO2, but allocated increasing amounts to the shoots at the expense of the roots as CO2 concentration increased. In contrast, NO− 3 -supplied plants allocated most of the Mn to the shoots. Ammonium-supplied plants typically allocated more resources to the chaff while NO− 3 -supplied plants allocated a greater percentage of elements to the roots.No other study to our knowledge has examined the influence of N form on plant nutrient relations at three different atmospheric CO2 concentrations. Overall, N form affected growth, total plant nutrient contents, and nutrient distribution in senescing wheat shoots, grain, and roots. The influence of NH + 4 and NO− 3 on growth and nutrient status were so distinct that they should be treated as separate nutrients and not bundled into a general category of N nutrition. Wheat size and nutrition at senescence responded to CO2 concentration in a non-linear manner. As was previously shown , we found that plants supplied with NH4 + were more responsive to CO2 concentration than those supplied with NO− 3 . Although not explicitly addressed here because of the heterogeneity of variances, interactions between CO2 and N treatments likely existed for a number of the biomass and nutrient measures. Most nutrient concentrations were generally higher in NH4 + – supplied plants, with the exceptions of NO− 3 − N, Mg, B, and Mn, which were generally higher in NO− 3 -supplied plants. Phytate, which hinders human absorption of Zn and Fe , showed little variation at ambient and elevated CO2 between NH4 + and NO− 3 -supplied plants, which, in conjunction with the observed greater bio-available of Zn in NH + 4 -supplied plants, may have consequences for human nutrition. Distribution of nutrients to the shoots, roots, chaff, and grain in response to CO2 concentration and N form was also non-linear and varied by nutrient. The data support our hypothesis that NO− 3 -supplied plants would show a more limited biomass and yield enhancement with CO2 enrichment than NH4 + -supplied plants. Nevertheless, mean biomass and yield decreased from ambient to elevated CO2 in both NO− 3 – and NH4 + -supplied plants in contrast to biomass increases in prior work on wheat seedlings . NO− 3 – supplied plants allocated more biomass to roots and had larger root:shoot ratios than NH4 + -supplied plants regardless of CO2 concentrations as has been reported previously , but increased root mass at elevated CO2 concentration for NO− 3 -supplied plants reported previously were not observed here.

There is also a growing concern about the effects of their environmental transformation products

The annual exposure values ranged from 0.32 × 10-3 mg for BPA-lettuce to 2.14 × 10-2 mg for DCL-collards for an average, 70 kg individual residing in the United States. To place these amounts in context, the values were then converted to either medical dose or 17β-estradiol equivalents. Both DCL and NPX are commonly available non-steroidal anti-inflammatory pharmaceuticals. Based on typical doses and the observed plant concentrations, an average individual would consume the equivalent of much less than one dose of these medicines in a year due to consumption of leafy vegetables, representing a very minor exposure to these PPCPs. However, it should be noted that DCL has proven ecotoxicity and NPX has shown toxicity in mixture with other pharmaceuticals , so a simple estimation may not encompass all possible human health effects. Both BPA and NP are industrial products known to have endocrine disrupting activity. Bonefeld-Jørgensen et al. calculated the Relative Potency of these compounds as compared to 17β-estradiol , an endogenous estrogen hormone, at activating estrogenic receptors. In Table 4.3, the exposure values of BPA and NP were estimated as E2-equivalents by dividing by their Relative Potency . When the calculated E2-equivalents of BPA and NP are compared with the Lowest Observable Effect Concentration for E2 , it is obvious that the even the highest expected annual exposure to these compounds by consuming leafy vegetables would not reach the LOEC. This rough calculation suggests that consumption of vegetables would be unlikely to influence an individual’s overall endocrine activity,container vertical farming though caution should be used when considering risk to susceptible population groups.

Moreover, it must be noted that the use of hydroponic cultivation likely resulted in greater plant accumulation of these PPCP/EDCs, in relation to soil cultivation, due to the absence of chemical sorption to soil organic matter and minerals. This likelihood, when coupled with the fact that most of the 14C in plant tissues was in the non-extractable form, implies that the risk from actual plant accumulation of these PPCP/EDCs by leafy vegetables grown in uncontaminated fields irrigated with reclaimed water may be negligibly small. On the other hand, bio-solids have been shown to contain some PPCP/EDCs at much higher concentrations than treated wastewater and plant uptake from soil amended with bio-solids may pose an enhanced human exposure risk. Also, given that many PPCP/EDCs may be preferentially distributed in plant roots as compared to above-ground tissues , the potential risk may be significantly greater for root vegetables such as carrots, radishes, and onions. The occurrence of these and other PPCP/EDCs in leafy and root vegetables should be evaluated in the field under typical cultivation and management conditions.Population growth, urbanization, and climate change have created unprecedented stress on water resources. The reuse of treated wastewater from wastewater treatment plants is increasing by 15% each year to help meet water needs . As of 2006, about 3.6 × 109 cubic meters of treated wastewater were reused in the U.S. each year for purposes including agricultural and landscape irrigation . Regulations on wastewater reuse are mostly concerned with pathogen and heavy metal contamination . However, numerous studies have shown that a variety of trace organic contaminants are present in treated wastewater, including pharmaceutical and personal care products and endocrine disrupting chemicals . Some PPCP/EDCs have unintended biological effects on nontarget organisms at low concentrations .The beneficial reuse of treated wastewater for agricultural irrigation introduces PPCP/EDCs into the soil environment, where they may be taken up by plants and cause human exposure by ingestion .

While a number of studies have examined the uptake potential of PPCP/EDCs, most studies only considered a few compounds, making it difficult to discern the underlying mechanisms. On the other hand, plant uptake has been extensively investigated for many pesticides and herbicides . Studies show that systemic pesticides are passively taken up through the transpiration stream , and greater transpiration leads to increased accumulation of non-ionic compounds . Many PPCP/EDCs are ionizable compounds that may exist partially as ions at an environmentally relevant pH . The ionic state of a compound greatly affects the compound’s interactions with plants, such as adsorption on root tissue, interaction with the cell membrane, and sequestration into plant compartments . In a recent study, Wu et al. examined multiple PPCP/EDCs and observed a strong correlation between plant bio-concentration of a compound and its pH-adjusted octanol-water partition coefficient , but did not address transpiration effects. Herklotz et al. and Shenker et al. suggested that movement through transpiration-driven mass flow of water was likely an important route for the uptake of carbamazepine, and Carter et al. suggested that transpiration differences between radish and ryegrass contributed to their differential uptake of carbamazepine, diclofenac,fluoxetine, and propanolol. However, to date researchers have yet to quantitatively evaluate the dependence of plant accumulation of PPCP/EDCs on transpiration. In this study, we measured plant accumulation and translocation of 16 PPCP/EDCs, including neutral and ionizable compounds, in 3 plant species grown hydroponically in nutrient solution. Plants were grown in growth chambers with different environment regimes to impose two distinct transpiration patterns. Losses of nutrient solution through transpiration were monitored throughout the 21 d incubation and the levels of PPCP/EDCs in plant tissues were measured at the end of cultivation. The effect of transpiration on bioconcentration or translocation was statistically evaluated for anionic, cationic, and neutral PPCP/EDCs. Knowledge of the interplay between transpiration and plant uptake is useful for identifying types of PPCP/EDCs, as well as weather conditions, that may have a relatively high tendency for plant accumulation and pose potential human health risks.

Three plant species were included in this evaluation. ‘Champion II’ tomato seedlings were purchased from Armstrong Growers and ‘Nevada’ lettuce seedlings were purchased from Do-Right’s Plant Growers at 3 weeks post seeding through a local nursery. ‘Danvers 126’ carrot was started from seed in commercial potting soil and seedlings were used at 26 d post-seeding. Two growth chambers with open circulating air were used in this study. One chamber was programmed to simulate a cool and humid environment with a day time temperature of 17 °C, followed by a night time temperature of 15 °C, while the relative air humidity was kept at 80%. The other growth chamber was programmed to simulate a warm and dry environment with a day time temperature of 27 °C, a night time temperature of 20 °C, with humidity at 50%. The cool-humid and warm-dry environments were used to induce distinctively different plant transpiration patterns. Both chambers received irradiation from a mix of incandescent and fluorescent bulbs, which gradually ramped over 7 h each day to a maximum light intensity of 300 µmol/m2 -sec2 which was maintained for 2 h before decreasing to darkness for a total daily photoperiod of 16 h. Six days before the start of the incubation,hydroponic vertical garden plants were carefully removed from their growth media, rinsed with DI water, inserted through jar lids, fitted with the foam collars, and placed in 2 L glass jars filled with fresh nutrient solution, at one plant per jar. After the plants were transferred to the growth chambers, jars were attached to a small pump system to aerate the solution with ambient air. After 3 d, plants were transferred into clean jars of fresh nutrient solution to replenish nutrients and minimize microbial growth. After a total of 6 d of acclimation, 4 replicates of each plant species in each chamber were randomly selected and transferred into clean jars with 1900 mL of fresh nutrient solution that was amended with 5 mL of a working solution of PPCP/EDCs prepared in ultrapure water. The nominal concentration was 1 µg/L for each compound in the nutrient solution, a level at the higher end of concentration ranges found in treated wastewater effluents . The actual chemical concentration of each compound was measured with solid-phase extraction, as described below. Plants were grown for 21 d in the growth chambers. Every 1 to 3 d, based on the amount of solution transpired, all plants were transferred to clean jars containing fresh solution fortified with PPCP/EDCs. At each solution exchange, the masses of fresh and used solutions from each container were gravimetrically measured to determine the exact amount of solution transpired by each plant. The total transpired mass was defined as the cumulative mass of nutrient solution removed from a jar throughout the 21 d incubation. Evaporation from jars was negligible due to use of fitted lids. The pH in the nutrient solution was measured at that time with pH paper; which was later used to calculate the average log Dow of each compound . At 21 d, all plants were removed from their treatment jars, rinsed with DI water, and separated into different parts.

For lettuce and tomato, plants were divided into leaf, stem, and root tissues. For carrot, plant was separated into leaf and root. Plant tissues were weighed, placed in self-sealing plastic bags, and then stored at -70 °C before analysis. To characterize the depletion of PPCP/EDCs in the nutrient solutions between solution exchange, solution samples were analyzed for levels of PPCP/EDCs on day 8 and 10. On day 8, freshly prepared nutrient solutions were analyzed for the initial chemical concentrations of PPCP/EDCs. To determine the masses of PPCP/EDCs remaining in the solution after 2 d of plant growth, the used nutrient solution from each plant container on day 10 was analyzed. To estimate the potential removal of PPCP/EDCs not attributable to plant uptake, triplicate jars of fortified nutrient solution without plants were included in each growth chamber for 2 d and then similarly analyzed. Prior to analysis, nutrient solution from each container was weighed and mixed by shaking, from which a 275 mL sub-sample was removed. The solution sample was extracted according to a previously published method . Briefly, 100 µL of surrogate solution was added to each sample. A Supelco Visiprep DL solid phase extraction manifold with disposable liners and HLB cartridges were used for extraction. Cartridges were sequentially conditioned with 5 mL each of MTBE, methanol, and water, and samples were loaded at 5 mL/min under vacuum. Sample vessels were rinsed with 200 mL of ultrapure water, and the rinsate was also passed through the cartridge. Sample cartridges were dried with nitrogen gas and then eluted with 5 mL each of 90/10 MTBE/methanol and methanol. The eluent was evaporated under a gentle stream of nitrogen at 40 °C to a volume of 400 µL and then transferred to a 2 mL glass vial. The condensing vessel was rinsed twice with 300 µL of methanol and the rinsate was added to the sample vial to make the final volume to be 1.0 mL for analysis.The extraction of plant tissue samples followed a previously published method . In brief, plant samples were removed from the freezer and immediately placed in a freeze-drier . Samples were dried for 16 h, or to dryness,and then weighed. Each plant sample was then finely ground in a stainless steel coffee grinder. The grinder was cleaned between samples using soap, water, and acetone. A 0.20 g aliquot was placed in a 50 mL polypropylene centrifuge tube and spiked with 100 µL surrogate solution. Samples were sequentially extracted with 20 mL MTBE, and then 20 mL acetonitrile, by sonication in a Fisher Scientific FS110H ultrasonic water bath for 20 min followed by centrifugation at 3000 rpm. The combined supernatant from each extraction step was decanted into a 60 mL glass tube and evaporated at 40 °C under a gentle flow of nitrogen to a volume of 0.5 mL. The residue was re-dissolved in methanol and then mixed in 55 mL ultrapure water. The SPE cartridges were conditioned with 5 mL methanol and then 5 mL water. Samples were passed through cartridges at 5 mL/min under vacuum, and then sample tubes were rinsed with 30 mL of ultrapure water, which was also passed through the cartridge. Sample cartridges were dried with nitrogen gas and then eluted with 7 mL methanol. The eluent was evaporated under a gentle stream of nitrogen at 40 °C to a volume of 200 µL and then transferred to a 2 mL glass vial. The condensing vessel was rinsed twice with 150 µL of methanol and the rinsate was added to the sample in the vial to create a final volume of 0.5 mL.

Microbial metabolism is a crucial process for the transformation of PPCP/EDCs in soils

While some compounds are readily degradable, their continual input causes these compounds to behave like pseudo-persistent pollutants . Direct, acute effects on wildlife are rare due to the low environmental concentrations typical of PPCP/EDCs. However, bio-accumulation of specific compounds in organisms creates the potential for toxic effects in susceptible populations. An example is the drastic decline of the South Asian vulture population, which suffered a species-specific toxicity to diclofenac in scavenged cattle carcasses . A wider concern is sub-acute toxicological effects . For instance, some fragrance compounds in personal products, such as polycyclic musks, as well as some cardiac pharmaceuticals, such as verapamil, have been shown to inhibit multi-drug transporters in cell membranes of aquatic organisms . These transporters are an integral part of an organism’s defense to xenobiotic compounds and their inhibition increases sensitivity to other compounds, like genotoxins . Selective serotonin reuptake inhibitors are a class of antidepressant pharmaceuticals that act by enhancing serotonin signaling in the brain by reducing reuptake of released serotonin. Low levels of SSRIs have been shown to initiate spawning in bi-valves and increase the aggression of subordinate lobsters, which may have subtle effects on ecological communities . Many PPCPs have non-specific toxicity mechanisms that require higher concentrations for acute effects , but EDCs act on specific cellular receptors of the endocrine system, and therefore even at extremely low levels can potentially cause toxicities by disrupting normal endocrine signaling . These compounds have varied modes of action, acting as agonists or antagonists for estrogen, androgen, or other receptors. For instance, bisphenol A and nonylphenol have agonistic effects on the estrogen receptor at cellular concentrations of 22.8 and 2.2 µg/L, respectively, and antagonistic effects on the androgen receptor at 137.0 and 550.9 µg/L, respectively ,vertical growing racks which are levels relevant to concentrations in treated wastewater and relevant to blood serum and urine concentrations in humans .

Exposure to bisphenol A, nonylphenol, and 17β-estradiol have all been shown to increase vitellogenin levels in fish and impact other endpoints like smolt development and survival . The endocrine activity of these and other PPCP/EDCs has contributed to detectable estrogenic and androgenic activity in WWTP effluent , which can cause increased vitellogenin levels and feminization in male fish exposed to effluent . Some of these effects have been observed in the environment , showing that current environmental levels of PPCP/EDCs are high enough to cause adverse effects in wildlife populations. Due to the nature of their environmental input, PPCP/EDCs usually exist as a complex mixture in environmental matrices. There is some evidence that these mixtures act additively, and perhaps synergistically, to elicit biological effects even at low levels . For example, the individual toxicities of the analgesics diclofenac, ibuprofen, naproxen, and acetylsalicylic acid were measured as 68 – 166 mg/L for Daphnia and 72 – 626 mg/L for algae, levels which are considerably higher than the typical ng/L environmental concentrations. However, when the 4 compounds were in a mixture, their toxicities were additive and the EC50 was reached at lower individual concentrations . While these concentrations were still in the low mg/L range, these results have implications for the potential toxicity of environmental matrices that may be contaminated by a multitude of individual PPCP/EDCs . There are also potential human health effects from PPCP/EDC exposures. While present at low levels, PPCP/EDCs are routinely detected in food, packaging, and other materials and the consumption of contaminated agricultural crops would contribute to the total exposure. Exposure to PPCP/EDCs may be detrimental to susceptible age and population groups . The potential impact of EDCs on developing organisms is especially concerning. As an example, cytokine secretion is an important process in human placenta tissue and disruption can lead to pregnancy loss. Nonylphenol was found to affect cytokine secretion in human placenta at cellular concentrations of 0.022 – 220 ng/L . Nonylphenol has been measured in human blood of non-occupational workers at 15.17 µg/L and in human urine at 1.57 µg/L , suggesting that humans are currently exposed to nonylphenol through environmental and other sources at levels sufficiently high to elicit this toxicity.

An emerging concern is the potential health effects of transformation products from the degradation of PPCP/EDCs in WWTP and environmental matrices . For many PPCP/EDCs, their complete fate in the environment and the types of transformation products formed are unknown. Of the limited information, some products of carbamazepine transformation in soil have been identified, which are known to have higher biological activity than the parent compound , a situation that was also known for nonylphenol ethoxylates . The effect on human health from unidentified transformation products with generally unknown behavior and toxicity requires further research. When treated wastewater, bio-solids, or manure is applied to soil, PPCP/EDCs may transfer into the soil compartment . Irrigation with treated wastewater may cause accumulation of PPCP/EDCs to higher levels in soil than in the irrigation water . An example is the 2.34 – 132 and 2.74 – 12.6 fold increase of mass in soils of the stimulant caffeine and the epileptic drug carbamazepine, respectively, as compared to the treated wastewater that was used for irrigation, suggesting accumulation from previous irrigation . bio-solids are applied to land less frequently than irrigation water, due to limitations on nutrient loading and run-off , which allows more time for PPCP/EDC degradation in between input events. Therefore, bio-solids applications typically result in lower levels in soil than in the amendment material .The potential of a compound in soil to be taken up by plants or transport off-site is largely governed by its partitioning between the soil matrix and soil-water. Weak sorption to soil implies enhanced mobility and availability, as in the rapid translocation of the antibiotic sulfachloropyridazine after land application, likely due to its low partitioning coefficient with soil . Adsorption of chemicals to soil is generally related to Kow . For example, in a leaching experiment, the antibiotic olaquindox was mostly recovered in the leachate while the more hydrophobic antibiotic tylosin was retained in the soil column . However, estimating partitioning coefficients from Kow may work well only for neutral PPCP/EDCs,vertical farming in shipping containers where hydrophobic partitioning is the dominant process. With ionizable PPCP/EDCs and in clayey soils, many other factors are likely to be important, including processes such as hydrogen bonding, surface complexation, and cation exchange . In addition, the partitioning behavior of ionizable PPCP/EDCs is highly susceptible to soil pH, as changes in pH may alter the ionic fraction. For instance, acidic chemicals have reduced affinity for clay minerals orsoil organic matter at pH levels above their pKa, resulting in increased availability and mobility .

Partitioning between soil and soil-water is best represented with Kd, which is specific to a compound and soil system and usually determined experimentally . Values can vary widely among soils and among compounds. For example, carbamazepine, diclofenac, and ofloxacin had log Kd values of 1.56, 2.21, and 3.55, respectively, in the same high organic content soil, but in a low organic content soil had values of -0.31, – 0.35, and 3.08, respectively . This specificity hinders the comparison of partitioning behavior between different compounds and different soils across studies. The calculation of a Koc value, by dividing a Kd by the organic fraction in the soil to produce an organic carbon content normalized distribution coefficient, has been used to address this limitation, although Koc values are available only for a limited number of PPCP/EDCs . Table 1.3 lists log Koc values for selected PPCP/EDCs. The persistence of the bio-available fraction of PPCP/EDCs in soil also affects their potential to be taken up by plants. This fraction is difficult to measure, so it is often approximated by the fraction that can be extracted using laboratory protocols . The time required for half of the extractable compound to dissipate is usually described with a half-life or 50% dissipation time , calculated by fitting the percent of a compound that is extractable at several time points to a regression curve or a first-order decay model . Soil half-lives for PPCP/EDCs can vary widely, ranging from hours, in the case of ibuprofen, to years, in the case of fluoxetine, depending on the compound and environmental conditions . One soil dissipation process for PPCP/EDCs involves sorption to the soil matrix and conversion to bound residue that is not recovered by solvent extraction procedures. Formation of bound residues is generally considered a decontamination pathway because the bound fraction is often unavailable for microbial metabolism or plant uptake . This has been shown to reduce or remove the toxicity of pesticides , but similar information is not available for PPCP/EDCs. The formation of bound residue involves several abiotic processes between a compound and the soil matrix, including hydrophobic partitioning, covalent bonding, ligand exchange, migration to micro-sites, and ionic bonding . The relative prevalence of these mechanisms is influenced by the characteristics of the compound and matrix, as well as the duration of compound exposure and concentration . In some cases it has been shown that a small portion of bound residue became available after a change in soil management or by mobilization by microbial metabolism or plant growth, but this may amount to only a few percent of the total residue . Because of the difficulty in assessing the bound fraction of a compound, many studies investigating this process use radio-labeled compounds, but this technique can be costly and is not available to all researchers. Another option is the use of a series of extractions employing progressively harsher solvents, though this approach makes it difficult to relate the various extracted fractions to bio-availability . The potential for PPCP/EDCs to form bound residues has been examined in a few studies. Fent et al. determined that about 80% of 14C-bisphenol A was quickly bound in 4 soils after a 3 d incubation, and the bound fraction persisted throughout a total of 120 d of incubation. Bound residues accounted for 44 – 78% of 14C-diclofenac after 40 d of incubation in a clayey silty soil and a silty sandy soil . Higher soil organic carbon content can enhance the formation of bound residues, which has been shown for diclofenac and carbamazepine . Overall, formation of bound residues is likely an important pathway to decrease the bio-availability of PPCP/EDCs in soil, although more experimental evidence is needed to validate the extent of this process for other PPCP/EDCs.In addition to abiotic processes, there is evidence that microbial activity is important in the formation of bound residues. Nowak et al. showed that 4.5% of ibuprofen was incorporated into fatty acids and amino acids of the soil biomass at 30 d, which decreased to 1.4% by 90 d. This decrease was attributed to population turnover, resulting in the incorporation of non-living fatty acids and amino acids into the soil matrix. Concurrently, at 30 d, 9.4% of ibuprofen was bound to the soil and at 90 d the bound residue fraction increased to 27.9%. Aerobic bio-degradation has been identified as the main route of transformation in soil for veterinary pharmaceuticals . Bacteria can directly use some PPCP/EDCs as growth substrate and can transform others through cometabolism . During cometabolism, the amount of soil organic matter may affect transformation rates since it acts as a substrate for overall microbial activity . Oxygen state affects the rate of microbial transformation . Under aerobic conditions, estrone had a half-life of 0.6 d in soil previously exposed to WWTP effluent, but under anaerobic conditions half-life increased to 6.3 d in the same soil . For triclosan, the effect of oxygen state was even more dramatic; its half-life increased from 5.9 d to 28.8 d. However, the degradation of 17β- estradiol was actually faster in anaerobic soils , showing compound specificity in microbial transformations. Other factors that affect the soil microbial community may also affect transformation rates of xenobiotics, including moisture content, temperature, amendment, and sterilization. For example, transformation of 14C-naproxen was inhibited in soils at cooler temperatures as compared to warmer temperatures . Degradation of naproxen was also reduced in air-dry soils as compared to soils at 15% or 30% water content . Prior exposure to a compound may also potentiate the transformation of a compound by selective enhancement of certain microorganisms .

This concentration was likely orders of magnitude higher than the environmentally relevant levels

The rhizosphere is usually considered an important player in the overall metabolism of xenobiotics by whole plants, as root exudates generally enhance the richness of microbial communities in the root zone, leading to a greater microbial abundance and accelerated microbial degradation.Although the rhizosphere in a hydroponic system may differ greatly from that in soil in terms of microbial community abundance, it was likely that some of the transformations of the target CECs or their TPs occurred in the solution due to rhizosphere-mediated microbial degradation.This could result in the occurrence of methylated or demethylated metabolites in the hydroponic solution and their subsequent uptake into the plant. In addition, previous studies also showed that some xenobiotics may be excreted from plant roots into their bathing solution. Analysis for the target CECs in the nutrient solution in this study, however, generally showed an absence of the corresponding methylation or demethylation products in the nutrient solution, except for acetaminophen and M-acetaminophen . The calculated compliance constants of the methylated CECs are summarized in Table 1, along with the calculated R-CH3 relaxed force constants. A stronger chemical bond is harder to break as it requires more energy, while it is easier to form as more energy may be released. The computation results of the relaxed force constants showed that the chemical bond strength between the methyl group and the major molecular fragment in the methylated CECs followed a general order of methylparaben < diazepam < naproxen < M-acetaminophen. Therefore,vertical garden indoor demethylation may be expected to occur more readily for methylparaben, but more slowly for M-acetaminophen.

Conversely, methylation of DM-methylparaben may be expected to be the hardest, while it is relatively easy for acetaminophen. The trends observed for the four pairs of CECs in A. thaliana cells generally followed the prediction from the bond strengths. For example, the demethylation of methylparaben in A. thaliana cells was the most extensive among the test compounds, followed by diazepam. In contrast, demethylation of M-acetaminophen or naproxen was negligible under the same conditions. Methylation from acetaminophen to M-acetaminophen was found to proceed more readily than the conversion from DMnaproxen to naproxen, while methylation of DM-diazepam was not observed. Due to the limited number of compounds considered in this study, a quantitative correlation between the calculated bond strength and transformation rates was not carried out. However, future studies may consider ascertaining such a relationship, with information from more compounds, in order to better understand the impacts of molecular structures on bio-transformation in plants. The demethylation and methylation processes involve distinct subfamilies of CYP450s, esterases and methyltransferases, which may depend on plant species specific enzyme activities, as well as the chemical structure of xenobiotics. The generally good agreement between the experimental results and bond strength-based predictions in this study suggests that evaluation of chemical characteristics such as the bond strength of R-CH3 may be used to identify CECs with a high tendency for specific transformation reactions. Given the large number of CECs, such a first-cut screening approach may be invaluable for developing a priority list of CECs that may undergo such conversions. The usefulness of such predictions may be further improved by considering more compounds and different plant species, and by developing and refining quantitative structural-activity relationships.To ensure confident identification and quantitative measurement of CECs and their TPs, an artificially high concentration was used in the growth media for A. thaliana and wheat seedlings.In addition, hydroponic cultivation was a simplified system, and the absence of soil should impart significant influences on the adsorption and hence the availability of CECs for plant uptake. Microorganisms in rhizosphere soil under field conditions likely play a great role in facilitating transformations of CECs, and therefore, the interconversion of CECs and their TPs in the soil-plant continuum may exhibit patterns different from observations from this study.

Nevertheless, results from the controlled experiments in this study clearly showed that plants can mediate transformations of CECs such as methylation and demethylation. In some cases, demethylated products were found at relatively high levels under experimental conditions. Given that a large fraction of TPs was likely non-extractable or conjugated, the actual occurrence of such transformations in plants may be much more pronounced than that detected in this study. Conjugated metabolites may become deconjugated upon ingestion, for example, by enzymes in the gastrointestinal tract, releasing bio-active molecules.The methylated or demethylated TPs likely retain or have even increased biological activity. For example, DM-diazepam , although a demethylated TP of diazepam, is itself a drug for treating anxiety. The addition or loss of a methyl group alters the physicochemical properties of a compound, leading to different environmental behaviors such as bio-accumulation, metabolism, and toxicity. For example, diclofenac methyl ether showed greater acute toxicity to aquatic invertebrates than diclofenac.Bisphenol A mono- and di-methyl ether also displayed greater developmental toxicity to zebrafish embryos than bisphenol A.Therefore, when considering the whole life cycle of CECs, e.g., along the entire human-wastewater-soil-plant-human continuum, such circular interconversions may effectively prolong the persistence of CECs and contribute to enhanced human and ecotoxicological risks, underscoring an urgent need to consider such interconversions for more comprehensive risk assessment. For the four pairs of CECs considered in this study, demethylation appeared to proceed more readily than methylation, and there were also differences among different compounds. A preliminary analysis showed a dependence of the methylation or demethylation rate on the bond strength of R-CH3 of the compounds. As CYP450s, esterases and methyltransferases are involved in the metabolism of many xenobiotics, CECs with similar functional groups like -OH, -OCH3, -NH-, and -NCH3- may also undergo the methylation and demethylation cycle. With more experimental observations, it is feasible to predict the likelihood of such transformations using basic chemical structures and molecular descriptors.

This is particularly valuable given that CECs and their TPs are numerous in numbers and identifying compounds or structural features conducive to interconversions constitutes an important first step to better understand the significance of this phenomenon for the overall environmental fate and risks of CECs.The occurrence of numerous contaminants of emerging concern in the effluent from wastewater treatment plants and impacted aquatic environments has been extensively reported.However, most research has focused on the parent form of CECs while generally neglecting their transformation products that are often in co-existence. Many CECs contain reactive functional groups, such as hydroxyl, carboxyl and amide groups, making them susceptible to various biotic and abiotic transformation reactions.Simple transformations, such as methylation and demethylation, have been observed in various environmental matrices for many CECs.For example, previous studies showed the presence of methylated TPs of triclosan and bisphenol A in wastewater effluents and receiving streams.The methyl ethers of tetrabromobisphenol A were formed in aquatic environments in the presence of background methyl iodide.Methylation of acetaminophen was observed in soil.On the other hand, demethylation is a major metabolism pathway for CECs in organisms. For example, after oral administration in humans, naproxen and diazepam are demethylated to 6-O-desmethyl naproxen and nordiazepam , respectively.Despite the fact that TPs seem to occur readily and co-exist with their parent forms in the environment,vertical garden indoor system the ecotoxicological consequences of such transformations have not been adequately considered. Transformations such as the addition or loss of a methyl group can significantly change a compound’s physicochemical properties, such as Kow that is known to influence its fate and bioaccumulation.Methylated products of diclofenac, BPA, and triclosan all displayed enhanced toxicity or bioaccumulation potential in aquatic organisms. In this study, we comparatively explored the behaviors of four typical CECs, i.e., acetaminophen, diazepam, methylparaben, and naproxen, and their methylated or demethylated TPs in Daphnia magna, by considering their bio-accumulation, acute toxicity, and interconversions. Quantitative structure-activity relationship models were further developed and used to describe the experimental results. The study findings highlight the importance of simple transformation reactions such as methylation and demethylation in understanding the overall ecological risks posed by CECs in aquatic environments. To further understand the effect of methylation and demethylation on the acute toxicity to D. magna, bio-accumulation of the CECs and their methylated or demethylated counterparts was measured in adult organisms. The concentrations of target compounds remained relatively constant in the aqueous media during the 24 h uptake phase, with RSDs ranging from 2.8% to 18.4% . Therefore, the mean measured concentrations of target compounds in the water phase were used as to fit Equations and to derive BCF values. The bio-accumulation kinetics of target compounds are shown in Figure 2. The concentrations of CECs and their methylated or demethylated TPs generally showed an increasing trend at the beginning of the uptake phase and reached an apparent equilibrium in 24 h.

Upon transferring the exposed D. magna to clean AFW to initiate the depuration phase, the concentration of test compounds gradually declined over time. With the exception of diazepam, methylated derivatives consistently showed much higher concentrations in D. magna than their demethylated counterparts. For example, after 2 h of exposure, the concentrations of acetaminophen and M-acetaminophen in D. magna were found at 308.7 ± 42.6 ng g-1 and 8730.7 ± 2900.9 ng g-1 , respectively, a 28-fold difference . This was consistent with the fact that methylated acetaminophen has a higher log Dlipw than acetaminophen . In addition, at pH 8.5, acetaminophen was expected to be partially ionized in the aqueous media, while M-acetaminophen should be completely in its neutral state . Methylparaben also displayed a much higher accumulation than DM-methylparaben in D. magna at the end of the uptake phase . The 3-fold change also coincided with the difference in log Dlipw between DM-methylparaben and methylparaben . The level of DM-naproxen in D. magna was below LOD, and therefore its bioaccumulation may be deemed negligible . In contrast, significant accumulation of naproxen in D. magna was observed, again suggesting a pronounced effect by hydrophobicity induced by methylation. It is also likely that DM-naproxen was rapidly metabolized due to the presence of an exposed hydroxyl group . The presence of the hydroxyl group in DM-naproxen may facilitate its conjugation with an amino acid or glucose in D. magna, contributing to its rapid metabolism and reduced bio-accumulation. Unlike the other three pairs, there was no significance in the bio-accumulation between DMdiazepam and diazepam in D. magna , with 6792.5 ± 1215.8 ng g-1 and 7599.7 ± 1470.3 ng g-1 detected in D. magna after 24 h, respectively. This may be attributed to the fact that methylation or demethylation does not result in a great change in their physicochemical properties and that both compounds have similar log Kow or log Dlipw values . The derived kinetic parameters of target compounds are given in Table S3. In general, the methylated derivative in each pair had a larger ku than the corresponding demethylated counterpart. The dynamic BCF values, calculated as the ratio of ku and kd, showed a strong correlation with the BCF values derived from the steady state , suggesting enhanced bioaccumulation for most methylated CECs. For example, the dynamic BCF of M-acetaminophen was 10.0 ± 0.0 in D. magna, which was significantly higher than the dynamic BCF of acetaminophen . For DMdiazepam and diazepam, however, the BCF values in D. magna were not significantly different from each other, which again coincided with their generally similar physicochemical properties. For aquatic organisms, increased bioaccumulation of contaminants is often attributed to a compound’s hydrophobicity, as bio-accumulation is driven by lipids in an organism and is positively related to hydrophobicity or log Kow for neutral compounds. Increased bioaccumulation after methylation was previously observed for diclofenac in aquatic invertebrates. Bioaccumulation of methylated diclofenac was found to be 25-110-fold that of diclofenac in H. azteca and G. pulex. In this study, methylation generally increased log Kow of CECs, and further log Dow and log Dlipw, although the relative increases are specific to the individual compounds. The generally enhanced bioaccumulation in D. magna was also in agreement with the effect of methylation on CEC bio-accumulation in plants.Methylation of CECs could occur in natural water bodies due to the presence of methyl iodide,during wastewater treatment, and during biological transformations in soil, plants ,and earthworms.Therefore, methylated derivatives of CECs may be prevalent in the environment and should be considered in a holistic risk assessment because of their different behaviors and biological activities, such as increased bio-accumulation potentials.

Two single benzenering metabolites of TBBPA were identified in pumpkin plants and rice cell cultures

Previous expression kinetics of CMG2-Fc in N. benthamiana suggested that protein accumulated in leaf increased from day 1 to day 6, supporting the first explanation. It is likely that kifunensine will remain stable even longer if longer incubation period is desired to maximize protein yield. Kifunensine is known to inhibit enzymatic activity of class I α-mannosidases, and thus should stop mannose trimming in the first place to yield single Man9 N-glycan structures. However, we observed multiple oligomannose-type N-glycans with mannose residues ranging from 3 to 9, although the most abundant structure was Man. This observation is consistent with cell culture kifunensine studies, where multiple oligomannose-type N-glycans were detected under kifunensine treatment. This could potentially due to the difference in inhibition efficacy of kifunensine towards class I α-mannosidases isoforms, which results in an incomplete inhibition of mannose trimming from Man9 structure. Also taking enzyme kinetics into consideration, depending on the ER concentrations of Man9 glycoprotein substrate, class I α-mannosidases, and kifunensine, enzymatic mannose trimming from Man9 could take place even if the amount of active ER α-mannosidase I is low. Although mannose trimming was not completely inhibited at Man9 structure, this method still showed the ability to significantly modify glycosylation using a simple bio-processing approach. It is likely that Man9 abundance can be further increased if treated with higher concentration of kifunensine, but it is not necessary if the goal is to eliminate the production of plant-specific complex N-glycans. Although in this case, CMG2-Fc can be purified easily from whole-leaf extracts through a one-step purification with Protein A chromatography, in many cases,vertical rack multiple steps of chromatography are required to purify a target protein from a large pool of host native proteins when a highly selective affinity tag is not present.

This could result in low protein yield and difficulties to achieve high purity, which is typically required for therapeutic recombinant protein products. Targeting proteins to the apoplast allows the collection of target protein in AWF, which contains much lower levels of plant native proteins than whole-leaf extract since only secreted proteins are collected, thus lowers the downstream process complexity. In this case, CMG2-Fc purity and concentration increased by 3.9-folds and 4.4-folds, respectively, when collected in AWF versus in whole-leaf extract. A similar trend was observed in kifunensine-treated samples, which confirms that kifunensine does not affect protein secretion, allowing secretion of CMG2-Fc with oligomannose-type glycoforms. The increase in purity and concentration was consistent with a previous study on harvesting a target protein from plant AWF. Hence, AWF collection is a feasible method for recombinant protein harvesting, which avoids contamination with intracellular host cell proteins, and is particularly valuable when target protein is hard to purify. Together with kifunensine treatment, apoplast-targeted recombinant protein without any plant-specific glycoforms can be transiently produced in N. benthamiana, and likely in other plants as well. Products can be collected at high concentration and purity from AWF, containing predominantly oligomannose-type N-glycans. Further studies should focus on determining how long the inhibition effect of kifunensine lasts after the one-time vacuum infiltration by monitoring the protein glycoform profile at multiple time points after vacuum infiltration, and the threshold concentration of kifunensine that results in a complete N-glycan shift from plant complex-type to oligomannose-type for other glycoproteins, particularly those with more N-linked glycosylation sites. In addition, the protein expression kinetics should be compared between kifunensine-treated and untreated groups to maximize target protein yield. Depending on the desired glycoform, this method can also be applied to other N-glycan processing inhibitors such as castanospermine, deoxynojirimycin, and swainsonine. Contaminants of emerging concern are chemicals and other substances with no regulatory standards but have been recently detected in the environment and have the potential to cause adverse effects at environmentally relevant concentrations.

CECs consist of many different types of chemicals based on their purposes of use, including flame retardants, pharmaceuticals and personal care products , endocrine- disrupting chemicals , nanomaterials, among others. Flame retardants such as polybrominated diphenyl ethers and tetrabromobisphenol A are added to manufactured materials to prevent or slow the development of ignition. Prescribed pharmaceuticals like amoxicillin and overthe-counter drugs like acetaminophen are widely used by individuals for personal health. PPCPs also contain many types of preservatives and anti-bacterial substances, like triclosan. Antibiotics and veterinary medicines are widely applied to improve the production of livestock. For a long time, these substances were unknown, unidentified, unexpected, or unsuspected pollutants due to limitations in analytical methodologies. It was also challenging to assess the impact of CECs on human health and the environment due to the lack of data or risk assessment tools. After emission from varied sources, including household sewers and industrial effluents, CECs are carried in contaminated wastewater to wastewater treatment plants . The removal efficiency of CECs during treatments depends on the design and performance of individual WWTPs, as well as the physicochemical properties of CECs.Many studies have shown that numerous CECs are present at trace levels in the treated effluent in the ng L -1 to µg L -1 range around the world, including Spain,Germany, the United States, China, and South Africa. The concentrations of CECs are generally higher in bio-solids because of the higher organic matter content, and are in the μg kg-1 to mg kg-1 range.For example, triclosan and triclocarban were detected at 2715 and 1265 μg kg-1 respectively, in bio-solids, in a study conducted in the U.S. The use of TWW and bio-solids in agriculture, and/or their direct discharge into the environment, can introduce CECs to agricultural ecosystems and surface aquatic ecosystems, posing potential risks to ecosystems and human health.Many CECs contain active functional groups such as hydroxyl, carboxyl, and amide groups in their chemical structures, and are susceptible to many biotic and abiotic transformations in the environment and organisms.

Transformation products of CECs can be directly introduced into WWTPs in municipal wastewater, leachates, and surface runoff. For instance, pharmaceuticals can be metabolized in the human body after consumption and are excreted in large portions as metabolites, particularly conjugates.TPs can also be formed during the treatment processes in WWTPs via microbial transformations, photochemical transformations and oxidation and halogenation by disinfection processes.These processes may also transform some TPs back to the parent CECs, such as hydrolysis/deconjugation of the conjugates of estrogens, leading to the “negative removal” for certain CECs in WWTPs.Transformations of CECs may also take place in agroecosystems and aquatic environments after TWW and bio-solids are discharged or applied. Soils,plants,terrestrial organisms,algae,aquatic organisms and photochemical degradation have all been reported to mediate CEC transformations. In some cases, TPs may pose higher ecological risks than their parent compounds, as they may have a greater bio-accumulation potential, increased toxicity to organisms, or longer persistence in the environment.Assuming the majority of irrigated TWW and applied bio-solids are received by soil, roots would serve as the major pathway for CEC uptake into plants.Mechanistic understanding of CEC uptake remains rather limited. Based on the current knowledge, root uptake of CECs occurs primarily through passive diffusion, although an energy dependent active process mediated by transporters is likely for certain hormone-like compounds such as naproxen, clofibric acid, hydrocinnamic acid and perfluoroalkyl acids.Translocation of CECs from roots to above-ground tissues, such as stems, leaves and fruits,vertical farming hydroponic has also been observed by previous studies, with concentrations of CECs generally being more substantial in roots.Both biotic and abiotic factors have been shown to affect the uptake, bio-accumulation and translocation of CECs by plants. These factors include plant physiology, soil pore water chemistry, the physicochemical properties of CECs, and the experimental conditions.Plant physiology plays an important role in plant uptake of CECs.Plants exposed to stressors such as drought, salinity and high temperature can respond with various adaptive mechanisms such as heightened antioxidant defense, hormone regulation, and metabolic modifications.The water and nutrient uptake and photosynthetic efficiency can decrease significantly in plants grown under stressed conditions.Therefore, it may be assumed that non-stressed plants have greater potential for CEC uptake and accumulation. Other than plant physiology, plant species within the same genus, even varieties of the same plant species, have shown different patterns of CEC uptake. For example, different carrot genotypes displayed distinct uptake patterns for metformin, ciprofloxacin and narasin.

Based on the current knowledge, the ability of crop plants to uptake and accumulate CECs in the edible tissues decreases in the following order: leafy vegetables > root vegetables > cereals and fodder crops > fruit vegetables.The physicochemical properties of CECs, such as hydrophobicity and speciation, can strongly affect their uptake and translocation in plants.Many CECs in TWW and bio-solids are polar compounds with low volatility and contain ionizable functional groups, like hydroxyl, carboxyl and amide groups.Only the dissolved CEC fraction in soil pore water would be considered available for root uptake.For neutral CECs, root uptake usually involves two pathways: 1) equilibrium between the aqueous phase in plant roots and the peripheral solution such as soil pore water; and 2) chemical sorption by the lipophilic root solids.Ionized CECs, on the other hand, may undergo disassociation in soil pore water depending on the solution pH.The electrical attraction or repulsion to the negatively charged root surface, along with the ion trap effects, which occur when CECs are neutral in the apoplast but ionized inside the cell , can greatly influence their uptake and translocation in plants.A linear relationship has been often observed between the hydrophobicity, e.g., log Kow, and the bioaccumulation of neutral CECs in plants.However, using log Kow to estimate the bio-accumulation of ionizable CECs is not accurate, partly because lipid bilayers can more easily accommodate charged organic species than n-octanol.Different experimental settings, such as hydroponic cultivation, greenhouse soil cultivation and field experiments, have also exhibited great influence on the uptake and accumulation of CECs in plants. Hydroponic experiments provide simplified conditions,while greenhouse soil cultivation and field experiments have more environmental relevance. The uptake of CECs by plants is usually evaluated by bio-concentration factor , which is calculated as the ratio of the concentration of CECs in plant tissues to that in soil pore water, or the growth media for hydroponic experiments. BCF values of CECs in roots can be high up to 840 L kg-1 in hydroponic settings, while the values obtained from soil experiments may be much smaller,suggesting the availability of CECs for plants decreased greatly in soil pore water during to phase partitioning. CECs with active functional groups, such as carboxyl, hydroxyl, and amide groups, are susceptible to metabolism in plants via various enzymatic activities after being taken up. This metabolic process is similar to the hepatic detoxification system and is known as the “green liver”.Three metabolic phases are usually involved in the metabolism of xenobiotics in plants: Phase I metabolism is an activation process that includes hydroxylation, dealkylation, oxidation and reduction, that are catalyzed by cytochrome P450s, esterase, peroxidase, or other enzymes to enhance reactivity and polarity of xenobiotics; Phase II metabolism is predominantly conjugation with polar bio-molecules, such as amino acids, sugars and glutathione, to further increase the hydrophilicity and mobility of xenobiotics; Phase III metabolism refers to the sequestration of conjugated metabolites in plant cells, including the storage in vacuoles and the incorporation into cell walls.There have been only a small number of studies focusing on the metabolism of CECs in plants. Plant cell systems, such as A. thaliana cell culture,carrot cell culture,rice cell cultures and horseradish hairy root cell culture,have been used as a simple and fast approach for characterizing metabolites of various CECs. Whole plants, either hydroponically cultivated or grown in soil, have also been used to understand plant metabolism of CECs. For example, phase I metabolites of carbamazepine, 10,11-epoxide-carbamazepine and 10,11-dihyro-10,11-dihydroxycarbamazepine, were observed in the leaves and fruits of tomato and cucumber, leaves and roots of sweet potato and carrot, and leaves of Typha spp.Diclofenac was found to be hydroxylated to 4’-OHdiclofeanc in barley,horseradish root cell culture and bulrush.Phase I metabolism was also reported for epimers of tetracycline in pinto bean leaves.Phase II metabolism has been found to occur extensively for some CECs in plants. For example, conjugation with amino acids was reported for naproxen,ibuprofen,diclofenac,and gemfibrozil in A. thaliana cells and whole plants.

The effect of bounce back appears to diminish with bidirectional QTL extension

Different execution strategies also make it difficult to compare validation results between papers. Additionally, there remain some problems with the RWR method, particularly its reliance on the known gene distribution, which is unlikely to reflect the true distribution of genes associated with the trait. It is also apparent that even with the bidirectional extension of QTL there remains a tendency to over represent the centers of chromosomes. Given the central importance of gene distribution to RWR, addressing this particular failing will produce a method that is much more effective at identifying QTL of interest, and will therefore improve the rate at which breeding and fine mapping can be accomplished. The probability associated with the selection of a particular marker, P, as the origin for a particular QTL is calculated by assessing the number of locations in the genome on which the QTL can be placed. P is determined by the number of markers that can be used as the origin O of the QTL of length L, a number which excludes all markers that would result in the QTL extending beyond the end of the chromosome. This origin-based model of QTL mapping is an approximation for the true process of QTL placement, wherein QTL are roughly centered on a marker and are terminated at a marker on either end which represent the 95% confidence intervals for that QTL. In the case where the original QTL were not terminated at markers, it is preferable to use a model in which the QTL is centered on the chosen marker. Models requiring that the QTL must both start and end on a marker are not feasible, vertical farming aeroponics because the distance between markers is not uniform; with this constraint, a QTL of a given length might have only one possible genomic location. Markers are used in a direction-independent manner to avoid under representation of the ends of the chromosomes.

Under the null hypothesis, the probability of using any marker is {0,1,2}/M, which can take on any value between 0 and 1, inclusive. Here, the numerator depends on whether the marker can serve as O with unidirectional QTL extension, bidirectional QTL extension, or with neither; M refers to the total number of markers from which the QTL can extend to the left plus the total number of markers from which the QTL can extend to the right . Although the denominator could be adjusted to take into account the fact that a single QTL can only be mapped to one chromosome, this is unnecessary, because a QTL is not equally likely to be mapped to every chromosome. To understand why, consider the most obvious strategy to account for differences in chromosome length and the number of usable markers: a weighting scheme. We would divide the number of usable markers on each chromosome by the total number of usable markers in the genome . If this weighting is then used to adjust the probability P of using any marker on that chromosome, which is already proportional to 1/MC, the chromosome-specific marker counts cancel out and leave only the whole-genome marker count. To best represent the topology of the genome, the SPQV simulates genetic loci by selecting genes at random from the whole genome gene distribution to represent the genetic basis of the trait of interest. The use of the whole genome gene distribution as a source accounts for the topology of the genome, including the decrease of gene density at the centromere and telomeres . This strategy assumes that the true distribution of genes associated with a particular trait is approximately the same as the distribution of genes on a whole, rather than the assumption used in the simplest instance of RWR: that the distribution of known, previously associated genes reflects the true distribution of genes associated with that trait. We argue that this novel assumption is more likely to be accurate because trait-related genes can easily be discovered in a spatially biased manner : tandem arrays promote clustered discovery, some transposons involved in transposon-mediated mutagenesis preferentially target certain sequences , and genes in regions close to the centromere tend to be difficult to identify through methods that rely on recombination .

Additionally, the genome is interconnected; many traits rely on the interaction between multiple, seemingly disparate biological processes. Use of a random distribution for simulating genes with the SPQV is also possible, but fails to capture the genomic topography. Because genes within functional groups are not randomly arranged, duplication events and gene clusters in the original set of known genes are taken into account by considering genes without a marker between them as one genetic unit. The SPQV values are clearly most similar to those produced by the RWR experiment that was closest to biological reality: marker-only QTL origins, bidirectional mapping, and no bounce back . This makes sense, as the SPQV method is designed as a smoothed version of an experiment with these characteristics. Restriction of QTL origin to the markers that were used in mapping leads to an increase in EGN for RWR . This effect occurs for all QTL lengths. It is likely that the increase of identified genes in the context of restricted QTL placement is attributable to the physical structure of chromosomes: the markers selected for QTL mapping have a similar distribution to the genome wide distribution of genes , and are therefore relatively sparse in gene-poor regions such as the centromere. Similarly, the use of bounce back leads to an increase in RWR identified genes for all lengths of QTL, though this increase is particularly noticeable for some of the larger QTL . It is likely that the relatively large number of genes situated close to the ends of chromosomes is the main contributor to the impact of bounce back on identified gene number. It is possible that this reduction is due to a smoothing of the distribution, as the occurrence of bounce back is effectively split in half over the two separate tails of the chromosome. The presence of long and short arms on chromosomes, and the corresponding lopsidedness of the gene distribution, might also contribute to this phenomenon .

The use of bidirectional mapping appears to result in fewer genes identified by RWR, though this effect is relatively minor when compared to the effects of origin restriction and bounce back. In spite of the prominence of dark colors on the left side of the heat map, the confidence intervals identified for small and medium QTL by the SPQV and by RWR are fairly similar regardless of RWR method . The CIs in this range were consistently far below 1 regardless of method. In all, the SPQV 95% confidence limit for small QTL tends to be slightly smaller than the one produced by the RWR method that takes the same biological realities into account . However, this makes little difference in practice, because they are both less than 1: because observed gene counts are integers, EGNs from either method will be rounded up . In other words, if an SPQV confidence limit is defined as 1.2, the QTL of interest must have an observed gene content of 2 or more genes to be considered significant during general use. For larger QTL, SPQV values tend to outsize those produced by RWR. These large QTL approach the size of a full chromosome, and can indeed be larger than several chromosomes within the S. italica genome. It is the authors’ opinion that this is not an overestimation for the true distribution of genes associated with the trait of interest, as the true distribution likely has more than the known number of genes. Because of this, significance is unlikely for very large QTL,vertical indoor hydroponic system except for in the case of a true distribution of genes that is extremely uneven at the chromosomal level. A reduction in tiller number is a classical domestication trait in maize . Modern maize lines have been bred to grow as single stalked plants to facilitate high-density planting, while the maize progenitor, teosinte, is highly tillered. The genetic network associated with tiller suppression is controlled by the teosinte branched1 gene that also controls several other aspects of maize morphology , including inflorescence and floral architecture. Several mapping populations made from crosses between the W22 maize inbred line and teosinte were recently described and used to map several domestication traits . As expected, several domestication traits associate tightly with tb1 pathway. Here, we use the QTL reported by Chen et al. 2019 to illustrate the utility of the SPQV. Only the QTL with the same effect direction in both maize/teosinte mapping populations were assessed. Seven genes closely associated with the tb1 pathway in maize were located in the Zm-W22 NRGene 2.0 assembly and analyzed using SPQV. Notably, these genes were selected based on their strong, known associations with the branching pathway in maize. Since only high-confidence genes can be used accurately with our method, if any gene were not truly associated with the trait of interest, its presence will render the SPQV more stringent than necessary.

The QTL identified for the traits BARE , EB , GLUM , KRN , STAM and TILN have previously been connected with the tb1 pathway in maize. These QTL were therefore assessed in relation to the seven genes in Table 1. The markers found in the W22 x TIL01 RIL sub-population were used to determine the base pairs associated with the CIs of these QTL. Where the end points of the QTL did not have an exact match to a marker, the next closest marker was used so as to mimic ‘extension’ style mapping. The results of this analysis are reported in Table 2-2. Four of the assayed QTL identified a gene from the tb1 pathway, corresponding to four out of six of the represented traits. If the various adjustments described in this paper are applied to the RWR-based assessment of QTL mapping experiments, a more apt confidence limit for the expected number of genes will be identified. These adjustments do not account, however, for all of the issues associated with the application of RWR to this particular variety of question. RWR not only continues to rely on the distribution of known genes, but also results in gene-count distributions that nearly always fail to meet the requirement for smoothness . These distributions, in other words, have a tendency to change abruptly, and are frequently binary in the case of small and very large QTL. The ‘unsmoothness’ of any given distribution will be exaggerated by small QTL size and short lists of known genes; a known gene list with fewer than one gene per chromosome, for example, would produce a binary distribution even for large QTL. Additionally, RWR continues to exhibit a reduced likelihood of the QTL falling in the regions [1,1+L] and [C–L, C] even with the adjustment for bidirectional QTL extension. Finally, a practical weakness of the application of considered RWR is that this procedure requires a great deal of thought, effort, and expertise, and there are many points in the procedure at which simple errors can produce dramatic changes in the confidence limits that are ultimately produced. In light of the flaws of naive RWR, and the complexity of making the suggested adjustments, we recommend using the SPQV to assess the quality of QTL mapping experiments. The function provided, SPQValidate, requires only a few lists of data; the function itself accomplishes the analytic work that might be a stumbling block in RWR. Many of the other problems inherent to RWR are overcome by the SPQV’s probabilistic nature. This tool is potentially overly conservative, however, in the case of short QTL. It is extremely unlikely that the SPQV will produce a value of 0 for the confidence limit, as any locus is likely to be within range of at least one marker for even the shortest identified QTL. Because of this, the minimum confidence limit is, in practice, 1, which might be misleading for small QTL. Additionally, the total number of genes in a QTL is not necessarily an authoritative measure of a QTL’s validity; one can imagine that a QTL located on a single gene of high impact might be considered non-significant if the SPQV is the only method of validation used.

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