Hemp Growing

Some methodological limitations should be considered. First, preexisting differences in neurocognition, which may increase risk for substance use , cannot be ruled out in this cross-sectional study. Second, given the studies suggesting decreased motivation associated with marijuana use , the observed cognitive differences may be due to amotivational influences on test performance. Third, we used composite scores for data reduction purposes, and although common practice, they may not reproduce in other samples. Fourth, results may not generalize to other samples with different lengths of abstinence, patterns of substance use , gender or ethnic distribution, or SES0parental income. In conclusion, the general pattern of results suggested that even after a month of abstinence, adolescent marijuana users demonstrate subtle deficits in psychomotor speed, complex attention, planning and sequencing, and verbal story memory compared with non-marijuana using teens. Increased frequency of lifetime marijuana use was also associated with decreased performance in these areas. Implications include the need for psychoeducation aimed at informing adolescents and parents of the potential long-term cognitive consequences of heavy marijuana use. Longitudinal studies are critical to help rule out premorbid influences on cognitive function and to assess the developmental trajectory of neuropsychological functioning among adolescent marijuana users over time.College-going individuals in the United States may have unique attitudes toward substance use behavior and tobacco use, grow vertical including shifts in attitudes and behaviors that are associated with the constantly changing product landscape of alternative tobacco products , such as electronic-cigarettes .

Psychosocial behaviors and campus culture, including class attendance, peer socializing, campus policies, and residential environments, may also facilitate these unique attitudes toward favorability of smoking among college subgroups, while also introducing a unique risk environments for tobacco initiation, uptake, transition, and use . In addition, part of the variation explaining these health behaviors may be influenced by the specific demographic and socioeconomic characteristics of a college campus population and community. Data from social media platforms are often used to self-report and publicly communicate health-related attitudes and behaviors . Young adults [ages 18–25 ] in the United States are much more likely than older populations to actively use social media, including popular platforms Twitter, Snapchat, and Instagram . Infoveillance research, which uses online information sources to detect trends about the distribution and determinants of disease, including health knowledge and behaviors, has been used to develop insights on numerous public health issues including infectious diseases, vaccination sentiment, opioid use disorder, mental health issues, and, relevant to the exploratory aims of this study, tobacco and alternative tobacco use attitudes and behavior . However, smoking-related discussions on social media tied to specific colleges with geographic specificity has not been widely investigated. Existing studies using social media to examine tobacco-related attitudes and behaviors in college aged populations have primarily focused on evaluating the impact of social media health promotion anti-tobacco campaigns, recruiting hard-to-reach college populations using social media platforms, and examining the influence of exposure to tobacco-related social media content and marketing on current and future behavior and use .

Other research on college-aged populations has focused on assessing tobacco initiation and transition of use patterns, particularly as new alternative and emerging tobacco products become available . Accelerating research using social media to assess tobacco-related attitudes/influences among youth has also been supported by U.S. Federal initiatives, including projects funded by the National Cancer Institute and U.S. Food and Drug Administration Tobacco Centers of Regulatory Science, which for have identified and characterized e-cigarette advertisements on image-focused social media sites and tobacco user experiences with little cigars and e-cigarettes as discussed on Twitter . Changes in local, state, and national health policy related to tobacco and other products smoked or used concurrently with tobacco and electronic cigarettes can also have an impact on attitudes and behaviors of these populations. For example, recent debate in the United States regarding the legalization of marijuana/cannabis may positively influence marijuana-related attitudes for college populations, who tend to skew toward more liberal policies regarding decriminalization, legalization, and increased access . Similarly, the 2019 outbreak of e-cigarette and vaping-related lung injury associated with products containing tetrahydrocannabinol may dissuade tobacco or THC use in certain young adult populations, particularly since they were most heavily impacted by the disease . Examining the changing public attitudes and behaviors of college-aged smokers is particularly salient for the State of California, USA. As of January 2014, all campuses in the statewide University of California system became tobacco free , and the California State University system followed suit in 2017 . In addition, voters in California approved Proposition 56 in late 2016, which added a $2.00 increase to the cigarette tax effective April 2017, with an equivalent increase on other tobacco products and electronic cigarettes . Voters in 2016 also approved Proposition 64, which legalized the use of recreational cannabis in November 2016 .

During this time, the popularity of e-cigarettes in the United States was increasing . These changes in policy and preferences underscore the interconnected nature of the Triangulum of tobacco products , including potential for dual-use, transition between products, and challenges associated with conducting surveillance and implementing cessation programs . This changing policy landscape supporting tobacco control measures, as reflected in the shift of California’s public university systems to become smoke-free, is a key impetus for this study. The ability of these colleges to eliminate on-campus smoking relies in large part on understanding past and existing knowledge and attitudes held by the campus smoking populations, along with their perceptions and behaviors that may be associated with compliance or non-compliance to smoke free campus policies. In response, this study conducted exploratory research on the popular microblogging platform Twitter. Specifically, we used big data, data mining, and geospatial approaches to identify and characterize tweets originating from Twitter users specifically geolocated at California 4-year university campuses. Our primary objective was to assess types of tobacco and ATP products mentioned by users, the distribution of user sentiment toward tobacco and smoking behavior, and to assess the feasibility of detecting self-reported smoking behavior that may represent a violation of campus smoke free policies. Secondarily, we also sought to conduct a cross-campus assessment to determine how these factors vary across different university and college communities and over time.The objective of the study’s data collection approach was to obtain a highly refined subset of tweets, which were both posted from college campus’ geolocated coordinates in California and also included user discussions about smoking, in preparation for manual review to more purposefully identify tweets that specifically discussed different types of tobacco and smoking products, sentiment of users toward smoking behavior, and selfreported smoking behavior on campus. Data were collected from the Twitter public streaming Application Programming Interface using the cloud-computing service Amazon Web Services . The public streaming API was set with filters to collect all tweets that included metadata containing latitude and longitude coordinates, initially with no filter for keywords. Tweets were collected continuously from 2015 to 2019. All tweets collected included the text of the tweet and associated metadata, including the date and time of tweets. The use of the public Twitter streaming API to collect data pre-filtered only for tweets including latitude and longitude coordinates represent a subset of all tweets posted during the time frame of the study.

There exists the potential for sampling bias associated with different Twitter APIs that are not representative of all Twitter data , grow racks and data filtered only for geocoded data may omit many conversations from college aged populations about topics, such as smoking, which may be linked to college-related user groups . Though resulting in a much smaller volume of data, our approach nevertheless allows for detection of tweets in specific geospatial bounds at the high resolution of latitude and longitude coordinates in the state of California. Therefore, by using this data collection approach, we were able to isolate tweets originating from geospatial coordinates within the formal spatial boundaries of all 4-year universities in California. To enable this geolocation, a basemap of California 4-year universities from the Stanford Prevention Research Center was obtained and cross-referenced. The SPRC’s basemap included a relational geodata base which classified polygons by college name. College areas were comprised of multiple polygons for different campuses and associated properties, though aggregation was conducted at the overall college level to enable comparison across different colleges. Tweets were then filtered for 37 keywords which were broadly related to tobacco-related topics, including the names and brands of different tobacco and ATPs and descriptive terms associated with smoking and vaping as expanded upon from those used in prior studies . Specifically, the following keywords were used: bidis, cigarette, cigarettes, cigarillos, cigars, cigie, class, dip, e-cig, hookah, huqqa, joint, JUUl, kereteks, Marlboro, Newport, njoy, pipe, roll-up, shag, smoke, smoking, snuff, snus, tobacco, vape, vaped, vapejuice, vaper, vapes, vaping, vapor, waterpipe, waxpen, and weed. The purpose of this keyword filtering was to better isolate smoking-related conversations from all other Twitter discussions occurring on college campuses. After tweets were manually reviewed to positively identify smoking-related conversations originating in these college campuses, a snowball sampling design was employed which compared the frequency of all non-keyword terms in “signal” tweets with the frequency of these words in “noise” tweets . This methodology resulted in the identification and querying for ten additional keywords: 420, 818, blunt, bong, cigs, kush, marijuana, roll, smell, and stoge.After isolating a corpus filtered for tobacco-related keywords in areas geolocated for California 4-year universities, four researchers trained in social media content analysis used an inductive coding approach to identify study characteristics of interest by manually annotating all tweets , following an approach also described in prior studies . Annotators had backgrounds in public health and had experience manually annotating social media posts for tobacco behaviors in prior published research projects . Manual annotation included: identifying the type of smoking product discussed ; assessing positive, negative, or neutral sentiment related to smoking behavior ; and identification of whether the tweet included first-person use or second-hand observation of smoking behavior. Table A1 contains further details about topics that were coded as valid and invalid for positive identification as a “signal” tweet. Tweets that did not express sentiment related to smoking were excluded from analysis of signal tweets. The primary objective of this approach was to conduct exploratory research into what tobacco and smoking products were being discussed by Twitter users at California universities, assess the overall sentiment toward tobacco and smoking by these users, and explore whether it was possible to identify self-reporting of tobacco use-related behavior . Four authors coded posts independently and achieved a high inter rater reliability for overall coding categories and equally high inter rater reliability for specific subcoding for tobacco , vape , and marijuana specific tweet categories. For inconsistent results and any discrepancies related to coding, all authors convened to discuss, confer, and reach consensus on the correct classification informed by the inductive coding approach outlined in Table A1. Analyses of variation across college campuses were limited to the top twenty colleges by tweet volume, as estimates collected from samples of tweets from other colleges may have been biased due to insufficient volume of tweets collected. A p < 0.10 was considered statistically significant for correlational analyses due to sample size limitation. Point density algorithms were used to visualize and detect geospatial trends. Analysis was conducted in R version 4.0.1 and geospatial visualization of data was done in ArcGIS Desktop version 10.7. This project was part of a broader study to examine college campus smoke-free policies using qualitative focus groups and examining social media data with the qualitative analysis approved by the Institutional Review Board at California State University, Fullerton .Data collection resulted in 83,723,435 geo-identifiable tweets located in the state of California in the 5-year period from 2015 to 2019. From these tweets, 1,381,019 originated from 88 CA 4-year colleges, with the five schools contributing the most tweets including UC Los Angeles , Stanford University , UC Riverside , University of Southern California , and UC Berkeley . Thirty-eight schools contributed over 10,000 tweets each, overall representing 89% of the entire corpus of CA 4- year college geocoded tweets. Of these tweets, 7,342 contained smoking-related keywords with approximately one third occurring after 2015. In total, smoking-related topics originating from all geocoded tweets in the state made up an extremely small proportion of all topics and tweets specifically geocoded for CA 4-year universities.

It should be noted, however, that propanil drift is known to cause significant damage to fruit trees and cotton, and the chemical was banned in some areas at one point in the 1960s . Both propanil and glufosinate achieved comparable control of the watergrass weed, prompting the authors to conclude that both are “options to control multiple-resistant watergrass. For these treatments to be effective in the long term, [watergrass] seed rain reinfestations still need to be much lower” . In other words, to control the weed in the future, multiple applications of each herbicide may be necessary, reducing the profitability of the transgenic system. In response to this conclusion, the second trial year included two applications of varying chemicals for each herbicide regime with two treatments of propanil on conventional M-202 rice in the rotate-mode-of-action regime and two treatments of glufosinate on the LibertyLink® plots. Two issues with regard to this year warrant mentioning. First, the initial planting of LibertyLink® seed showed poor germination and was reseeded at 17 days after submergence . The additional reseeding costs are included in Table 8. Second, the researches mistakenly applied 350 g AI/ha of glufosinate in the first application rather than the recommended 500 g AI/ha. This presumably decreases both yields and costs, ceteris paribus, although watergrass control was still estimated at approximately 99.99 percent for this treatment regime . The economic results show that the intensive combination regime based on herbicide tank mixes is economically inferior with very small returns relative to the others due to relatively large herbicide material and application costs and little yield advantage.

The propanil treatments again outperformed the transgenic regime in terms of yields and returns with advantages of 11 and 6 percent, respectively, vertical grow racks despite significantly higher herbicide costs. However, seeding costs for the transgenic variety were twice as high due to the reseeding. The authors of the watergrass study attributed this poor germination to “the experimental nature of the LibertyLink® rice seed used in this experiment” . If the same yield results could be obtained without reseeding, the transgenic variety would dominate the alternative treatments with net returns of approximately $237.39, 11.8 percent higher than the next best alternative . Furthermore, the transgenic regime offered better control of watergrass than the rotational treatment . The 2001 growing season offered the opportunity for the third and final year of the Fischer project. No propanil treatment regimes were included in this final year, and all but the transgenic regimes used multiple applications of chemical herbicides. Given the germination problems in the previous year, the seeding rate of LibertyLink® rice was increased from 1.5 to 2 pounds per acre and these increased costs are reflected in the results presented in Table 8. Of the four treatment regimes compared in this year, the transgenic variety offered the highest returns—2 percent above the next best option . The intensive combination offered the highest yields but lowest economic performance due to the high cost of herbicide material and applications. It should be noted that, even with the higher seeding rate, the continuous glufosinate regime with LibertyLink® rice in this final year offered the highest returns of any of the years. Perhaps more significantly, when taken as a three-year program of management, the regime offered returns that were 72 percent, 68 percent, and 1 percent greater than the continuous-molinate, intensivecombination, and rotation-mode-of-action regimes.

However, the undiscounted difference between the two best alternatives is $9.20 per acre, part of which would likely be as a technology fee. The authors of the Fischer study concluded the following in their 2002 final report: “Overall, the use of glufosinate on transgenic LibertyLink® rice has demonstrated its potential as a viable strategy for the control of thiocarbamate-resistant watergrass.” The economic results presented here, based partially on those findings, suggest that a transgenic weed-management strategy can be, at the very least, competitive with alternative pest-control regimes such as herbicideaction rotation. Overall benefits of such a program, however, are subject to individual growing conditions, market acceptance, and the pricing strategy of the technology owners.Most commercial rice production in the Sacramento Valley region is cultivated under flooded conditions and is heavily dependent on chemical herbicides and insecticides to control weeds and insect pests. Release of the standing water into the Sacramento Valley watershed is thus an important negative externality arising from rice farming and one that may be affected by introduction of transgenic varieties.19 For example, in the early 1980s, a large number of fish were killed as a result of molinate poisoning in rice water drainage areas while small levels of thiobencarb were found to adversely affect the taste of drinking water . These findings led to implementation of the Rice Pesticides Program by DPR in 1983 . The program was originally designed to reduce molinate and thiobencarb pollution of local waterways and expanded in the early 1990s to include performance goals for these and the insecticides methyl parathion and malathion and to address damage done by drift and dust from aerial application of herbicides . Other chemicals such as bentazon have been prohibited or at least restricted in geographic use as in the case of propanil . Furthermore, the Central Valley office of the California Regional Water Quality Control Board passed an amended conditional waiver of waste discharge requirements for irrigated lands in 2003.

This waiver tightens quality standards for water released from agricultural uses in the Central Valley as well as requires monitoring and reporting of water quality and implementation of management practices that improve the quality of discharged water. Coverage under the conditional waiver can take the form of a “coalition group” with a common interest, such as the rice industry, and CRC has indicated that a commodity-specific rice waiver is preferred . Efforts to obtain this specific waiver are ongoing and have been received favorably by the board given the success of the rice pesticides program . Many of the chemicals currently registered for use on rice in California require holding periods for floodwaters that range from four to fifty-eight days in length and vary by water-management system . Ideally, these programs allow the chemicals to degrade in the water, resulting in ambient concentrations at least 90 to 99 percent less than the initial application . While these programs are generally effective in holding ambient concentrations at monitoring stations at or below maximum allowable levels, with some exceptions, significant holding periods can affect water depth and salinity within farms and thus initial establishment of rice plants and yields . The program has been quite successful; peak molinate concentrations have been reduced by better than 90 percent in the Sacramento River and Colusa Basin Drain since the beginning of monitoring and thiobencarb concentrations have declined as well, although by a lesser percentage . It should be noted that peak concentrations are an imperfect indicator as weather events and other sources of variability can significantly affect detectable levels of these chemicals. The environmental and health effects of leaching and runoff of chemicals in U.S. agriculture are diffi- cult to quantify, grow roon design primarily due to measurement issues and uncertainty. Approaches to estimation of these external costs vary and include using abatement or clean-up costs directly; developing proxy variables for environmental damage, including pounds of AI applied or indices of chemical properties; and assuming a dollar value per unit of damage. Contingent valuation methods have also been used to estimate consumers’ willingness-to-pay to avoid exposure through risk reduction . Although admittedly simplistic, one proxy for environmental damage is total pounds of chemicals applied. Based on 2002 acreage and use figures from DPR and the chemical labels, approximately 17.2 million pounds of herbicides were applied that year with 3.86 million pounds of active chemical ingredient. As shown in Table 3, total pounds of chemical herbicides applied per acre are expected to decrease by at least 84 percent with adoption of the HT system and total poundage of AI is predicted to decrease by at least 87 percent under the two-treatment scenario. Cultivation of HT rice could thus decrease total herbicide poundage by between 7.27 and 10.9 million pounds and AI poundage by between 1.69 and 2.53 million pounds, assuming 50 to 75 percent adoption. However, this simple measure ignores toxicity, mobility, and persistence of different chemicals in the soil and water that are likely to significantly affect external damage costs . Similarly, the mandatory water-holding periods currently in place are designed to dissipate the damage done by conventional chemicals.20 While this study makes no attempt to further quantify the reduced chemical damages from adoption of transgenic rice, several other projects have addressed the relationship between water quality and HT crops and are summarized in Gustafson. Computer-simulation models used by the U.S. Environmental Protection Agency  have predicted lower levels of chemical concentrations in runoff from transgenic corn systems than from conventional corn production. Furthermore, the herbicides used in the transgenic system have a “favorable chemical profile” in that EPA’s water-quality standards allow for greater concentrations of these chemicals in water than the traditional herbicides used in conventional corn production . Case studies cited in Gustafson for Bt cotton, HT corn, and HT soybeans confirm these results since concentrations of herbicides in watersheds were well below standards for a number of diverse geographic areas. We conclude that, while most, if not all, pesticides applied in agricultural systems introduce some degree of risk and thus potential damage to the environment, the reduced application rates and chemical properties of glyphosate and glufosinate have the potential to further reduce external damage costs from rice production. In addition, production benefits, specifically in terms of yields, may be enhanced if the holding period for floodwater is reduced for the transgenic system due to the lowered toxicity of the associated chemicals. This is in accordance with previous studies that concluded that cultivation of transgenic crops, in general, is consistent with increased environmental stewardship . However, it should be noted that these conclusions are based on the assumption that weeds resistant to currently available chemical controls in California do not exhibit this property towards glyphosate and glufosinate. As with many chemical agents, repeated applications of the same AI on the same plot may result in self-selection of weed varieties resistant to that ingredient, thus potentially reducing the environmental benefits of transgenic-crop cultivation in the long run as producers increase applications or shift to alternative means of control.This study has used a static, partial-budgeting approach to estimate the potential net economic grower benefits associated with adoption of one cultivar of GM rice in California. Scenarios were developed based on average cost data and actual pesticide-use data, as well as on a three-year field study of herbicide resistant weeds. Sensitivity analysis was conducted using both deterministic and stochastic methods to represent heterogeneity across growers and uncertainty regarding modeling assumptions. The results suggest that a production strategy including GM rice varieties could lead to significant economic benefits for many growers in at least the near term. Those most likely to benefit from adoption of transgenic rice are growers with relatively high herbicide material and application costs, likely as a result of weed resistance, and those who are restricted to certain chemical agents as a result of state or national regulations. Field-trial results suggested that a transgenic weed-management strategy over multiple years is competitive with a rotational strategy under certain assumptions and dominates a continuous-molinate and intensive-herbicide regime. These findings are generally consistent with ex post transgenic crop analyses for corn, soybeans, and cotton, most of which show positive or neutral economic benefits from adoption . In addition, water quality degradation is not likely to occur with transgenic rice adoption as chemical-application rates are expected to sharply decline and the toxicity of the associated chemicals is generally less than more traditional herbicides. We must point out that this study has certain limitations. First, these results are based in large part on ex ante assumptions regarding outputs and inputs, especially the relatively lower cost of glufosinate herbicide per gallon relative to the alternatives. It is expected that Bayer CropScience will set the price of glufosinate in accordance with its portfolio of transgenic crops , so the introduction of transgenic rice will not affect the price of this herbicide.

Growers characterized some aspects of government regulation to be outof-date with current technological trends and emphasized that government intervention has not played an active role in expediting precision weeding technologies. Though both VCs and startups called out economic development funds and locally-supported R&D tax credits, both stakeholder groups did not consider these government interactions to be as effective as industry-led programs. Another theme that emerged regarding the second objective is that the ideal role of government should be more hands-off because companies should find success in the free market. Some did bring up the benefits of clearly defined funding opportunities to reduce the friction of growers seeking government funding. A study using financial datasets of over 32,000 companies found that subsidies were only effective for short-term innovation while tax credits were favorable on both short and long terms . Subsidies are direct fiscal measures where the government is the project decision maker whereas tax credits are indirect fiscal measures whereby companies can choose their own projects and the direction/purpose of the innovation activity . However, all interviewees agreed that tax credits and subsidies should not be the primary driver or business case for precision weeding adoption. Government support should only fill in initial financing gaps as startups works towards achieving economies of scale.Interviewees from all stakeholder groups brought up the grower preference for equipment ownership, vertical grow racks going against service-based business models. Some precision weeding startups are using or have tried in the past to employ the weeding-as-a-service, recurring revenue model, whereby customers pay the startups for each instance of the service of weeding.

Owning equipment is preferred, especially accounting for the time sensitivity of some agricultural operations. Additionally, government loans and incentives, such as USDA Farm Service Agency Direct Farm Ownership Loans, help growers enter long-term leases or purchase their own equipment. Because of this strong equipment-owning preference, grower skepticism towards a weeding-as-a-service business model can hinder the growth of precision weeding startups. However, literature shows that recurring revenue models, as opposed to the direct sales model, have the advantages of significantly lower capital costs and lower payments compared to traditional loan structures, especially considering that weeding equipment remains idle for the majority of the year . Furthermore, subscription models give growers access to the newest and latest technologies, sharply decreasing the replacement cycle periods . These two revenue models are also not binary: recurring revenue models can derisk the use of new precision weeding innovations, with an initial subscription service proving the value of the technology, before growers transition to purchasing the equipment at the end of the contracting period . Beyond one-time purchasing and recurring revenue models, shared equipment pools managed by grower cooperatives and/or community organizers can derisk growers trying expensive technologies. An expansion of informal peer-to-peer networks, cooperatives can own equipment on behalf of their members and operate at cost. Non-profit or community-based organizations and equipment sharing businesses can also provide such services . Though growers typically prefer equipment ownership, case studies on equipment sharing arrangements, particularly in Europe, have assuaged timing-related fears. For example, a Swedish cooperative used 20 years of data to calculate the economic losses from performing a field operation at a sub-optimal time.

Their results found that the cost savings from shared equipment still outweighed ‘timeliness costs’ . In addition to the non-purchase option that cooperatives provide, contractor services can also be a mode for equipment deployment. The contractor does not necessarily have to be the manufacturer . Instead, equipment dealers or other businesses can train third party technicians and offer contractor services. In fact, Bavarian small scale farmers preferred both contractor services and shared equipment models over equipment ownership and working directly with the manufacturer . Despite such literature proving a preference for cooperative sharing pools, the interviewees of our study did not express similar views.The third objective regarding the user journey of growers adopting precision weeding technologies examined grower and startup concerns and touch points from awareness to continued use and advocacy. Both startups and growers emphasized in-person networks as the most important touch point and platform by which growers learn about new technologies. The influence of peer-to-peer networks brings up the question of perceived social risks: studies have shown that farmers who believe in combating climate change in their operations are concerned about the risk of negative social perceptions and thus reduced access to peer-to-peer networks . In this study, many Northern California farmers implemented climate adaptation farm management practices, such as water-effective irrigation. However, many remained sensitive about the negative political/social framing of climate change, strongly justifying their environmental adaptive actions with co-benefits, such as economic efficiency . Additionally, in a pollination management study in Michigan, researchers uncovered several large advice networks in which growers can reach other growers and their partners in a maximum of two to three hops and that 26 % of all communication mapped was from grower-to grower . In our study, growers cited word of-mouth from their peers as one of the key touch points influencing their journeys through the awareness, consideration, and purchasing phases.

Because many startups lack direct connections with growers, growers may look towards their peers to vet potential startup partners. In addition, aligning with Petersen-Rockney , the competitive landscape of specialty crops lend itself to the high stakes of intra-stake holder dynamics and social perceptions.For the first objective about the compatible motivations between precision weeding stakeholders, we found that the most common motivator was labor concerns, which was cited by 13 out of 17 interviewees. Some stakeholders added additional details about the labor pressures of organic farming in California, the competitive labor market, the hiring budget difficulties because of California’s increasing minimum wage, and the role of precision weeding technologies in increasing the efficiency of labor. Other commonly cited motivations were costs and precision weeding’s potential to ‘transform agriculture.’ Answering the second objective of collaborative models between stakeholders and their limitations, we found that the grower-identified blockers to adoption included competition between growers, oldschool mentalities such as equipment ownership, and a lack of connection between startups and growers. Additionally, startups and VCs also mentioned and expanded upon the growers’ urge to own their own equipment, coming into conflict with the weeding-as-a-service business model that some startups have ventured into. The startups agreed with the limitation that some startups lack connections to growers and suggested a few solutions: hiring employees who have worked in the agricultural industry and have local connections and startups developing strategic alliances with committees of growers. Both startups and VCs discussed their symbiotic relationship: VCs provide startups with portfolio support to accelerate business growth and mature company governance in exchange for equity. Exclusive to the agricultural industry, some VCs spoke to their role in providing startups on hands-on, agriculture-related support such as building a grower advisory board. All three stakeholder groups had varying opinions of the role of government in the precision weeding ecosystem. While all agreed that government-funded university research and the UC Cooperative Extension were helpful, pipp racking growers and startups viewed all tiers of government as being out-of-touch with grower needs and not providing enough R&D support to accelerate the adoption of precision weeding. The growers’ distrust of government is consistent with existing research. Regarding the third objective about the grower user journey, the most common touch point identified in the growers’ awareness phase was in-person networking, consistent with existing research about the influence of peer-to-peer networks in spreading information. Most of the areas of improvement were in the consideration/piloting phase, such as educating growers about misperceptions towards weeding-as-a-service business models, such as lack of equipment availability. As for the study’s limitations, the experimental design purposely was exclusively semi-guided qualitative interviews, as opposed to a mix between interviews and surveys, to examine in-depth perspectives and experiences. A limitation inherent in this experimental design was a lack of breadth, as the stakeholders interviewed in this study did not thoroughly represent the entirety of California’s precision weeding ecosystem, especially considering our focus on only three stakeholder groups. Future research could expand beyond our interview approach to include willingness-to-pay surveys to ascertain grower attitudes towards precision weeding. In addition, future research can broaden our research objective of compatible motivations to develop joint value propositions.

Better aligned value propositions will help startups communicate with growers and may influence startup R&D direction to better suit grower needs. Another limitation we faced with the interviews is that the agtech investing space, particularly for investors who have interests in California agriculture, is quite small. Because ‘all VCs know each other,’ some venture capitalists we interviewed or reached out to interview had concerns about anonymity and/or having diverse-enough viewpoints. Additionally, government outreach proved difficult with many potential interviewees canceling after learning about the informed consent conditions. However, this limitation was not a significant hindrance as the three core stakeholder groups did not include the government. This does raise a potential future research direction that more directly examines agriculture-related government endeavors and public-private collaborations. A limitation in an aspect of our data collection method was concerns regarding interview standardization. Though we followed a guide of pre-prepared questions for each objective, some interviewees cut the interview short while some were very generous with their time. The shortest interview was twenty-three minutes while the longest one was over an hour and a half. Therefore, in our results, we only featured stakeholder group maps, not individual maps. The broader implications of the study are for the governmental role of encouraging new technologies and the usage of cognitive mapping for agtech ecosystems. Precision weeding technologies respond to grower needs with conventional weed management. Resulting from labor pressures, the rising costs of chemical inputs, and market and government pushes towards environmental sustainability, California growers are pursuing alternative techniques such as buying machinery from new precision weeding startups. However, the adoption of precision weeding technologies is at times hindered by negative growers’ perceptions of startups and new technologies. In addition, despite strong public sector involvement in other digital agriculture sectors, this study found relatively low government involvement in precision weeding. Therefore, the policy implications and our recommendations are less on the regulatory side, but more so for governments to have a soft role in shaping standards and establishing legitimacy for new technologies. The cognitive mapping presented in this study can be applied to other emerging agtech ecosystems. Because most venture capital firms that invest in precision weeding also invest in other agtech startups or industry-agnostic hardware/deeptech startups, the interactions between agtech startups and venture capital firms may remain similar. However, future research may find varied interactions between the startups and growers. A future research direction may apply the same stakeholder mapping/qualitative interviewing methodology to other emerging agrifood technologies in regions outside of California. Like precision weeding technologies, crop harvesting robotics for specialty crops have achieved impressive prototypes in academic settings . Because of the similar high hardware costs and relatively low on-field use throughout a season, single-purpose autonomous robots are a suitable candidate for this study’s methodology. A study examining autonomous robots for soft fruit cultivation in the UK discovered that labor shortages are driving farmers to become interested in and optimistic about the potential of autonomous robots in picking, disease treatment, and harvesting . While our results found that growers were cognizant of the limitations and lower technology readiness levels of the startups’ initial prototypes and were sometimes willing to adjust their expectations accordingly, some studies have shown a deeper involvement between these two stakeholder groups at this early demonstration/piloting stage. For example, a project in New Zealand had been researching collaborative design efforts for a robotic apple harvester. Because orchards must be ‘robot-ready,’ such as having denser rows with trees lying flat against trellises, researchers found that some orchardists have been adjusting their landscapes accordingly to accommodate future technology adoption . Beyond leafy greens and fruit orchards, site-specific management is ideal for the heterogeneous nature of vineyards and our study’s methodology can be applied to precision viticulture. As the technology and user readiness of precision agriculture hardware develops, stakeholder mapping canidentify gaps in the existing ecosystem and offer both public and private entities opportunities to develop mechanisms that accelerate technology adoption.

My colleague’s argument that interventions based on behavioral theory do not work is flawed. He equates “behavioral interventions” with “theoretical basis”, and therefore claims theory-based interventions do not work because behavioral interventions have not been shown to work. As I argued in my opening statement, it is important to make a clear distinction between interventions based on behavioral theory, those merely ‘inspired’ by behavioral theory, and those that do not encompass theory at all. My colleague fails to make this distinction, and ignores evidence demonstrating the efficacy, and effectiveness, of interventions demonstrably based on behavioral theory in real world contexts. A further problem with his argument is to cite evidence of population-level non-change in rates of non-communicable disease and health-related behavior as evidence that behavioral theory does not work in the real world. It’s a poor argument without foundation. This is typified in his argument that the 25-year “falling or flatlining” of physical activity participation is somehow illustrative of a failure of behavioral interventions. This inference, which is speculative, is based on survey data on sport in which no intervention is identified. To make matters worse, this argument also infers that population-level changes in sport participation should reflect a desirable health-related outcome, a position he himself has argued against . He also argues that considerable flux occurs in individuals’ behavior over time while a “steady state” is generally observed, suggesting that behavioral interventions capture this “volatility” rather than actual change. Yet, no evidence on theory-based behavioral interventions is offered to illustrate this point – the “Get Active: Get Healthy” campaign he cites, best way to dry cannabis a sport-oriented intervention without basis in behavioral theory, provides no relevant data to verify this claim.

Researchers designing trials of behavioral interventions are all too aware of the issue of time-dependent variability in health behaviors, and include appropriate covariates in their analyses to demonstrate intervention effectiveness is in spite of, not because of, population-level variation in behavior. However, better evidence than that cited by my colleague supports his contention that population level change in health behaviors has not been achieved. Behavioral scientists’ should shoulder some of the blame for this failure by not advocating better implementation of effective interventions, but so too should all involved in the ‘chain of development’ of behavioral intervention from basic research to implementation. My colleague also argues that: “Behavioral theory can provide neither the explanation…on the wider causal systems that underpin… behaviors such as low physical activity and poor diet”. This argument is incorrect, my colleague probably equates all behavioral theories as theories of individual behavior, which reflects a deficient knowledge of behavioral theory. Many behavioral theories incorporate socio-demographic, structural, and group-level variables as determinants of behavior, and propose how they interact with psychological determinants. Similarly, my colleague argues that: “Undoubtedly, it is the focus on the individual rather than the population that undermines the real-world effectiveness of behavioral theory.” I agree that a simple causal narrative, such as a sole focus on individual behavior change , will not be effective in reversing population-level incidence of non-communicable disease. However, this is not a failure of behavioral theory per se; many theories encompass individual, structural, and ecological determinants of behavior. Rather, it points to a need to incorporate interventions based on behavioral theory into policy and practice through advances in implementation science.

Finally, my colleague suggests that theory-based behavioral interventions target only the motivated. This is not a new argument, intervention designers have been aware of this problem for years, and it is a problem that pervades most interventions, regardless of their theoretical basis. However, this is not the case for all interventions, and some of the most effective interventions work in changing behavior independent of motivation and in ‘real world’ contexts without the strict controls associated with laboratory research. In conclusion, I commend my colleague for identifying the need for more effectiveness trials and translation efforts for theory-based behavioral interventions. However, his arguments against the effectiveness of behavioral theory in ‘real world’ contexts reflect an acute lack of understanding of behavioral theory, are based on incorrect inferences regarding behavioral theory, fall back on emotive language in an attempt to persuade, make no practical suggestions on the way forward for behavior change, and, as a consequence, should be summarily dismissed.The arguments for behavioral theory barely warrant rebuttal. The volume of evidence presented for effectiveness demonstrates that those who receive behavioral theory interventions show changes in behavior compared to those who do not. This is evidence of efficacy, not effectiveness, a distinction not well understood in the literature. The appeal to implementation science is an attempt to extend controlled efficacy trial environments into implementation, focusing, for example, on maximising intervention fidelity to achieve an illusion of effectiveness that is impractical, uneconomic and largely futile for achieving behavior change at scale. Finally, the litany of under-funded and unsustained interventions, which are presented as a result of poor communication by behavioral theorists and poor understanding by policy makers, suggests behavioral theorists are collaborating in their own victim narrative.

Investment in implementing interventions has not been sustained because interventions have not been shown to be effective. But worst, because “implementation science” has sought to extend the controls of phase II and III efficacy and comparative efficacy trials into implementation, opportunities have been squandered to upgrade evidence by conducting genuine phase IV observational, non-interventional effectiveness trials in naturalistic settings.Behaviors change regularly and often. In England, circa 18 million adults change their sport participation each year, yet population sport participation levels have remained stable for quarter of a century. Shifting the curve of population behaviors requires an entirely different approach than changing individual behavior. Successes in the former include the use of seatbelts, and reductions in drink-driving and in smoking in public spaces, but they result from legislative mandating, not effective behavioral theory interventions. Since the 1960s in England, tobacco advertising, and then tobacco sponsorship, was regulated, restricted and then banned, followed by increasing restrictions and then a ban on smoking in public spaces, with a ban in cars and rented social housing now also being considered. Latterly, warnings then graphic images of increasing severity and size have been required on tobacco products, which now cover the whole packaging. Legislation has regulated messages and mandated behaviors, including mandated engagement with efficacious fear appeal interventions to ensure intervention fidelity and deliver effectiveness that would not otherwise be possible. Now, 50 years on, society no longer supports the social practice of smoking, and not only is the tobacco industry not permitted to reinforce smoking as a desirable behavior, it is required to undermine it. The role of behavioral theory in this process has been minimal; success is attributable to understanding the meanings attached to smoking as a social practice, the ways in which it is reinforced, and to addressing social and economic causation through incremental legislative mandating that disrupts the social practice of smoking.The academic practice of the development of behavioral theory shows the signs of paradigmatic science. Theorists become self-reinforcing and self-referential devotees, advocates for theory rather than outcomes. Empirical deficiencies are attributed to imprecise specification or poor implementation, prompting calls for more meticulous use and more controlled implementation, or for tweaks at the margins of theory. Social ecological approaches, which co-opt social perspectives to support existing individualistic behavioral solutions, weed drying rack rather than to interrogate and understand social and economic causation, are an example of the latter. Kuhn suggests these circumstances create the structure for scientific revolutions, in which empirical deficiencies can no longer be explained away at the margins or blamed on methods, and the old paradigm is displaced in favour of a new approach. I propose that new approach should be a social practice framework that deploys legislative mandating as a tool to disrupt social practices, underpinned by understanding of social and economic causation.

This should displace the current dominant individualistic behavioral paradigm that provides solutions that are not connected to causes. It’s time to burn down the house: the time for revolution is now!Although the current debate has showcased our different perspectives, it has also highlighted points of agreement. We both agree that interventions based on behavioral theory are efficacious in changing health-related behaviors. We also agree that there are problems with current evidence for the effectiveness of behavioral interventions, but we disagree on the nature and extent of these problems and their implications for drawing conclusions about the ‘real world’ effectiveness of behavioral theory. Beyond this, we also disagree on the implications of the evidence base as it stands for advancing effective, long-term solutions to the increasing prevalence of non-communicable diseases.While evidence for real world effectiveness of interventions based on behavioral theory applied in real world contexts is limited, it is not absent. Good examples of theory-based interventions that have demonstrable real-world effectiveness in changing behavior exist . Behavioral interventions offer a range of strategies that, if appropriately implemented, can and will make lasting changes in behavior at the population level. However, I recognize the need to develop the evidence base of effective large-scale behavioral interventions that can be embedded within existing networks, and are sensitive to the social and cultural norms of the target population. The interventions need to be sustainable through, for example, their incorporation into routine care or standard practice.Those developing interventions need to actively engage and lobby policymakers and governments to invest in interventions with demonstrated effectiveness and include them as core components of existing services. Behavioral interventions should be an integral part of a co-ordinated set of strategies that also includes policy change and legislation targeting change in specific behaviors at the population-level.Fundamental change is required: a paradigm shift to focus on social practice rather than individual behavior. Evidence that behavioral theory interventions are genuinely effective among those offered them, rather than simply efficacious among those receiving them, is all but absent, and absence of evidence is evidence of absence. The effectiveness gap is one of engagement that cannot be bridged by persuasion, rather mandating is required, either through legislation, or through interventions with mandatory engagement, such as point of choice information. Nonetheless, there is a role for behavioral theory: firstly, in providing efficacious support for individuals wishing to change; secondly, as a minor dimension of a social practice approach, which places historic and contemporary social and economic forces that lead to the existence of social practices, and that sustain them, at the centre, rather than the contemporary behaviors of individuals. Social practices can be disrupted over time through the incremental interplay of legislative mandating, and social change that creates the conditions for legislation. However, the circumstances and pace of disruption are rooted in understanding social and economic causation, and how this underpins the distribution and acceptance of behaviors in a population, not in aggregative attempts to effect individual behavior change.In commercial agriculture, weeds threaten effective crop production by competing with agricultural crops for resources , depleting soil nutrients, and interfering with agricultural operations, such as harvesting. In addition, weeds may serve as hosts for pests and pathogens, disrupting crop production. In 2017, over 400 types of pesticides were used in the United States, amounting to over one billion pounds . Despite the prevalence of pesticides, weed management for specialty crops still faces significant issues due to the increasing number of herbicide resistant weeds. In addition, weed management in high-value specialty crops encounters a unique challenge: the hesitancy of herbicide registrants to specify specialty crops on herbicide labels due to financial liabilities . Due to concerns associated with herbicide application, such as increased herbicide resistance and a growing demand for organic production, manual hand weeding has become an essential strategy in weed management. However, the expenses and difficulties of hand weeding make it one of the greatest weed management constraints that California growers face. The labor rates are impacted by recent California state legislation that increased the minimum wage to $15.00 per hour in 2022 and $16.00 in 2024 . Moreover, as a result of California Assembly Bill 1066 , the overtime threshold, defined as the hours of work required before employees receive overtime benefits, in the agricultural industry has decreased to 40-h weeks and 8-h workdays in 2022 . Because of these increased labor protections, on-farm labor has increased in cost, and for organic crops and high-density planting, hand weeding can cost more than $280 per acre for romaine hearts in the Central Coast .

The abatement potential of EVs over ICEVs and HEVs, when modeled using high resolution grid emissions rates, is highly nuanced and time dependent. Investigating this nuance and the barriers and opportunities it creates pertaining to commercial EVs is a main contribution of this research effort. Grid emissions attributable to EV charging generated by our simulations are compared to tailpipe emissions from conventional and hybridized gasoline and diesel vehicles. Fuel consumption was calculated using the combined fuel economy of each vehicle type and vehicle miles traveled. CO2 emissions were calculated using the CO2 emitted from burning one gallon of gasoline and diesel .For this Phase II effort, the team leveraged the proven power of the system-of-systems model developed and described in detail in the Phase I report to explore emissions resulting from a series of distinct scenarios for charging events of electrified commercial vehicles. The model was produced in MATLAB/Simulink and enables the integration of three sub-system models enabling in turn comprehensive, quantitative simulations of EV deployment for multiple driving cases under varying charging schedules and grid emissions assumptions. The architecture of the Simulink model is displayed in Figure 2-6. The initialization code, written in MATLAB, may be found in the Appendix. The current version of the model does not automatically account for charging losses occurring during the transfer of energy from the charging infrastructure to the electric vehicle’s battery system. These losses were corrected in a post-processing step wherein each total cumulative emissions output from the simulated charging events was multiplied by 1/η. Following the findings by Channegowda et al and assumptions employed by our Phase I report, cannabis grow setup we selected η=0.88 for Level 2 and η=0.90 for Level 3 charging systems. Simulation results are presented in the following sections.

These, as with the team’s Phase I results, represent what is believed to be an innovative method leveraging new data that yields a distribution of projections for CO2 emissions across a variety of assumptions and plausible scenarios.Table 3-3 depicts the cumulative energy consumption in kWh for each vehicle type included in the study at different levels of daily VMT. These values are a primary input for the simulations, informing the model as to what quantity of energy must be replaced during a charging event to return the battery to its full state of charge. To ensure consistency of comparisons, simulation outputs were only collected for scenarios where the battery was fully recharged during the charging event. Figure 3-1, Figure 3-2, and Figure 3-3 serve as comparative visualizations of simulation results for light-duty truck emissions rates in kilograms of CO2 per kilometer. Each plot depicts relative emissions rates for a battery-electric truck under different emissions profiles and level 2 charging schedule assumptions for each VMT level at different times of the year. Emissions rates are plotted along with emissions from an ICEV baseline as well as an HEV to enable comparisons. The plots represent additional corroborating evidence in favor of several pertinent takeaways from our Phase I study. The daily variance of electrical power grid emissions rates resulting from the switching on and off of dispatchable marginal generation resources by the grid operator in anticipation of or in response to evolving demand for power is high, especially during summer and winter months when temperature fluctuations are expected to be more extreme. Using monthly or annual average emissions rates fails to account for the nuanced fluctuations of real-world grid emissions rates , implying the true environmental benefits of EVs compared to ICEVs or HEVs are often misrepresented.

Are environmental benefits then over- or understated? The directionality is not uniform. Vehicle use, charging patterns, and seasonal fluctuation of grid characteristics play important roles in determining actual environmental outcomes, positive or negative.The above figures reveal that in these cases at least, employing hourly grid emissions rate data to guide inquiry into environmental benefits of EVs, while still at a higher resolution than annual or monthly average rates, minimizes the variation of marginal resources. As was concluded in the Phase I report, EVs are likely to require marginal resources en masse because they act together to force demand projections out of the expected regime, especially at growing rates of adoption. This Phase I conclusion is presented with the caveat, however, as Phase I dealt with personal EVs as opposed to the commercial EVs we are concerned with here. Still, this conclusion may well hold for commercial EVs, especially concerning the commercial applications explored in this phase of our research. The nature of many residential services, moving companies, and refuse operations is to operate during daytime hours , leaving the largest window of logical charging times for the evening or overnight hours with the occasional exception. If most commercial vehicle activity occurs during the day, then most commercial EV charging will occur overnight. During a transition period of EV adoption growth, utilities will be able to accommodate the associated generation demand to support commercial EVs, but these needs will most likely be met by marginal resources. This has implications when considering the environmental benefits of commercial EVs because marginal resource emissions rates possess the highest temporal variations. When using marginal grid emissions rate assumptions, the per-kilometer emissions of a battery-electric light truck traveling 20 miles per day were found to vary by as much as 131% depending on the charging schedule used .

Table 3-4 reports the percentage improvement of CO2 emissions for an EV relative to an ICEV in the light truck category, assuming 20 miles per day of business use, under various charging profiles. Note that studies that assume an average CO2 emissions rate may predict a very different environmental impact than studies that take certain marginal dispatch factors into account. Simple shifts in charging times that may have little impact on existing business operations may have sizeable impacts on emissions attributable to charging events, indicating substantial value for managed charging implementation.While the Phase I study explored mostly passenger cars, as presented above, this study built upon it to explore light trucks in service fleet operations. Next, we turn to Medium Duty EV use cases, which appear to hold much near-term promise, and may be financially attractive without significant subsidies. Presented in Figures 3-4, 3-5 and 3-6 are simulations of CO2 emissions for a Moving Truck application of various vehicle miles traveled during three principal seasons . While in some cases the variation in emissions rates for the different scenarios can be quite high, it is important to understand the cause and implications. For the scenarios with more VMT, there is a proportionally greater quantity of energy that needs to be replaced during the charging event. This can have the result of moderating the variance in emissions compared to shorter VMT scenarios. We infer this is because the emissions intensity of the electricity being used to charge the EV’s battery pack is diluted the longer it is being actively recharged. At smaller levels of energy displacement, the vehicle’s battery can be recharged entirely within one or several hours of charging. If this charging occurs within peak hours or whenever the carbon intensity of the grid and its marginal resources are highest, then the subsequent carbon intensity of the EV is similarly high. During longer charging events replenishing greater amounts of energy to the vehicle’s battery, the charging event is likely to last beyond periods of peaking grid carbon intensity resulting in the deposit of less carbon-intensive electrical power to the battery for at least some of the charging event. This mechanism holds implications pertinent to commercial EVs, whose larger battery capacities, greater rates of energy consumption, and generally higher VMT necessitate longer charging events. Commercial EVs may have more opportunities than private light-duty EVs to reduce the carbon intensity of their operations by charging across periods of high and low grid emissions intensities alike. Still, pipp mobile systems the demands of business may predicate faster charging times to keep vehicles on the road and minimize range and scheduling anxieties.

Growing penetrations of Level 3 systems would reduce charging times, raising carbon intensities absent charging management programs. The MD moving truck example for the various VMT cases, EV charging profiles and marginal emissions assumptions demonstrates that more research may be valuable to quantify with greater certainty how each of these factors can influence fleet emissions. Now is a particularly important time to evaluate these factors, as many MD EV cases are in a growth stage based on market and policy considerations. The foregoing is also contingent on trends in emissions for grid generation. While it is beyond the scope of this study to forecast how grid generation will evolve to meet new demands, it is important to co-develop tools that can simulate the associated CO2 impacts of different EV and grid growth scenarios. As was the case with the personal vehicles in Phase I, there exists a future threshold of commercial EV penetration that will trigger a realignment of the existing trends observed in grid emissions. Commercial EVs demand more power on average than private vehicles and therefore will have greater effects on marginal emissions trends. Increased power demand at common charging times will give rise to additional marginal resources, which are likely to be fossil in nature, at least in the near-term. The range of results depicted in the various scenarios across a range of vehicles suggests that all key stakeholders may ultimately benefit frombetter foresight to charging events on both short term and longer-term time scales. Thus, the ability to manage charging events becomes an essential part of the suite of regulatory levers and cyber-physical infrastructure that can facilitate effective growth of commercial EV deployments. Efforts to optimize the benefits of managed charging seem to depend upon the effective acquisition, analysis, and conveyance of high-resolution information concerning EV charging and its various externalities between system users, grid operators, and policymakers. This research, by way of integrated systems modeling and use case simulation, argues that using averaged emissions rates, especially at lower temporal resolutions, may obscure information. By refining the temporal resolution of the input data for both charging events and grid generation profiles, stakeholders can be better equipped to optimize environmental benefits from EV growth, as well as inform business decisions, and guide policymaking.In the near- and intermediate-terms, coordinated EV charging is a critical component of an effective transition to battery-electric vehicles for a growing range of use cases. The prevailing generation dispatch mechanisms and physical constraints of the electrical power grid are inherently sensitive to shifting demand trends and require consideration of hourly factors. These sensitivities are expected to heighten as electrification increases from a multitude of sources, including not only EVs, but other intermittent, seasonal, and continuous loads . Anticipating the timing and magnitude of demand spikes, such as those resulting from EVs, is necessary from multiple time domains. First, as we have stated, an hourly or even sub-hourly view of charging and grid dispatch may be important to ensure emissions benefits are understood. And second, from a resource planning perspective, grid operators seek to optimize dispatch and infrastructure funding decision-making processesover a much longer time scale. Thankfully, a number of support policies and Federal funding resources are stimulating new R&D, pilots, and demonstrations at the intersection of grid modernization, charging communication protocol, smart charge management, EVs, and the increasingly distributed grid in order to mitigate unintended demand peaks resulting from both higher current charging and higher penetration of EVs.In our simulations of CO2 output, hybrids performed on par with many EVs under marginal grid emissions scenarios. The recent EV policy environment included monetary incentives like tax credits to offset the relatively high purchase prices of EVs over their ICEV counterparts. This research may suggest that hybrids can provide some important benefits in parallel with EV growth, including reduced environmental impacts, and opportunities to reduce infrastructure investments by leveraging existing assets. It is also quite clear that a diverse fleet mix may provide certain strategic advantages, and that “winner take-all” policy architecture may be unwise. This research therefore emphasizes the need to conduct comparative studies as policy options are explored. Doing so can ensure that public dollars are more effective in reducin the imacts of transortation while maintain in the current expectations in performance. This can also help inform public and private investment decisions and accelerate paths to scale and impact.

Cattle are not affected by the toxins but humans may be severely impacted. Goats, sheep, feral pigs, and deer are also considered animals of significant risk for shedding E. coli O157:H7. Others, such as elk, coyotes, and raccoons, have also been shown to harbor this pathogen. Other wild animals, including birds, can acquire the bacteria from various sources, serve as a transient reservoir, or mechanically vector E. coli O157:H7 bacteria across a landscape. Although relatively limited in scope, studies assessing the seasonal association of E. coli O157:H7 in wildlife have generally concluded that the prevalence is very low or generally not detected in most regions studied . However, when there is a local potential source of E. coli O157:H7, such as a nearby dairy operation or feedlot, the prevalence can be much higher, and transmission between plant and animal agriculture may be demonstrated by genetic matches in isolates from the source and in associated rodents and birds visiting both areas . The two most common ways that E. coli O157:H7 can be spread from cattle into the environment and agricultural landscapes are through the land application of raw, uncomposted manure and through runoff of manure or lagoon water into streams and irrigation ditches. Bioaerosols of buoyant fine particulates have been suggested as another probable source of localized spread. Implementation of good agricultural practices as defined by the commodity specific food safety guidelines for the production and harvest of lettuce and leafy greens will help minimize risks of contamination of crops with E. coli O157:H7 . For hedgerows, the GAPs for leafy greens will likely require periodic monitoring of fields adjacent to wildlife habitat, cannabis drying system both for evidence of intrusion by animals of significant risk for carrying E. coli O157:H7 , as well as smaller known or potential vectors such as rodents and birds.

Presence of these smaller animals may also indicate the attraction of predators, such as coyotes, also shown to be potential vectors. If there is evidence of intrusion by animals, the production block must undergo a detailed food safety assessment by appropriately trained food safety personnel. The Salmonella spp. food safety issue is essentially the same as that for E. coli O157:H7, but the focus tends to turn to habitat for birds, reptiles, rodents, and amphibians. Apart from reptiles, in some areas, the prevalence and frequency of transmission again tends to be low except in association with significant point sources such as dairy, poultry, cattle, and swine production operations. However, Salmonella seems to have a much more prevalent environmental phase, so there is building evidence for a baseline that one is unlikely to escape. Hence, a mitigation treatment to reduce the threat of salmonellosis is needed if tolerated by the crop . Although much research remains to be done on the epidemiology of E. coli O157:H7, hedgerows around farms may actually help reduce the risk of E. coli O157:H7 by helping to trap and filter harmful pathogens in dust and irrigation or storm water runoff .Endemic and invasive weeds are important management concerns in California due to their direct and indirect costs to agriculture, the environment and society. Pimentel et al. estimated that weeds cost U.S. crop producers and pasture managers over $30 billion in control-related expenses and reduced productivity. Although specific data are not available for California’s portion of these losses, weed management costs for the state’s 40 million acres of crop and grazing lands, as well as the remaining 60 million acres of land area, amount, undoubtedly, to several billion dollars annually. In addition to the direct cost of weed control and lost agricultural productivity, weeds also affect ecosystem quality and function, reduce recreational access and degrade aesthetics in natural areas, change wild land fire regimes and severity, and impede water flow through rivers and canals, among other negative impacts.

Although crop weeds are seldom considered as being “invasive” in the traditional sense, novel biotypes can develop, spread and subsequently occupy a greater proportion of crop acreage than might normally be expected. For example, when a weed population evolves resistance to an herbicide or any other control measure, a “routine” pest can become a new and serious problem. The first case of an herbicide-resistant weed in California was reported in 1981 by UC scientists ; in recent years, additional species have evolved resistance to various herbicide chemistries used in some of California’s signature cropping systems, including flooded rice, orchards and vineyards as well as nearby non-crop areas.Environmental factors and production practices influence species composition at any location, a phenomenon known as selection pressure. Under constant conditions, the weed community will become dominated by species that thrive under those conditions. If this steady state is upset by a change in management practices, a weed shift may occur, resulting in a community dominated by different species adapted to the new conditions . This weed shift can be caused by agronomic and horticultural practices or by the use of herbicides, which are very strong selective agents. Some species will be less susceptible than others to any management practice, and repeated use of the same control strategy can shift weed populations to become dominated by naturally tolerant species . Herbicide resistance, on the other hand, implies that a genetic change has caused a formerly susceptible population of a species to become resistant to an herbicide. Herbicide resistance arises from the process of adaptive evolution, whereby mutations change the physiology of plants in such a way that the herbicide is less effective. Under the continued selection pressure exerted by the herbicide, resistant plants with the new genotype are not controlled, and their offspring build up in the population .

Depending on the initial frequency and genetic basis of resistance, the regularity and rate of herbicide applications, and the reproductive system of the weed, it may take from a few to many generations for resistance to become. The strongest selection pressure for herbicide-resistant weeds tends to be in modern, high-intensity agricultural cropping systems due to a high reliance on herbicides. According to the International Survey of Herbicide Resistant Weeds , since the first confirmed report of a resistant biotype in 1957, herbicide-resistant weed biotypes have been reported in at least 60 countries and include more than 400 unique species-herbicide group combinations . The United States has more herbicide-resistant biotypes than any other country , and California accounts for 21 of these . Worldwide, resistance to acetolactate synthase –inhibiting herbicides and photo system II –inhibiting herbicides are the most commonly occurring among weedy species. However, in recent years, glyphosate resistance and multiple resistances have also emerged as major problems in some cropping systems. Interestingly, while herbicide resistance in the United States as a whole is primarily found in broadleaf weeds, California has more herbicide-resistant grasses or sedges than broadleaf species . Due to the extensive use of preplant and in-season tillage in some agronomic crops in California, drying rack for weed along with the use of pre- and postemergence herbicides, herbicide resistance is not as widespread as it is in other parts of the country where no-till and minimum-till systems have been widely adopted. Reduced tillage systems are heavily reliant on a few herbicide modes of action and have correspondingly larger problems with herbicide resistance . In contrast to the rest of the United States, where herbicide resistance problems are centered on agronomic crops, the greatest problems with herbicide resistant weeds in California are in orchards, vineyards, flooded rice, roadsides and irrigation canal banks. Herbicideresistant weeds have become especially challenging problems in California’s signature cropping systems, which are characterized by little or no crop rotation due to soil limitations or long cropping cycles and relatively few opportunities for mechanical weed control. Although large by specialty crop standards, the approximately 3 million acres devoted to orchard, vineyard and rice production in California is a small market for herbicide manufacturers; thus, herbicide options are somewhat limited. Combined, these factors have led to a high degree of selection pressure for herbicide-resistant weed biotypes as well as weed population shifts to naturally tolerant species .In order to combat complex issues such as herbicide resistance, organized collaborations between weed scientists and other agricultural researchers with a wide array of expertise are required. This includes the activities of UC Cooperative Extension farm advisors and specialists, Agricultural Experiment Station faculty, support scientists, research staff and graduate students, as well as faculty from other universities and agricultural industry representatives .

Current herbicide-resistant weed management efforts range from applied research and extension efforts to basic plant biology and evolutionary ecology studies. Although the specifics vary, these efforts can be grouped into three general areas: applied management of herbicide-resistant plants, physiology and mechanisms of resistance and biology, ecology and evolution of herbicide resistance. Applied management of herbicide resistant plants. Many cases of herbicide resistance in weeds are identified after growers, land managers or pest control advisers observe weed control failures with treatments that were once effective. These weeds are generally brought to the attention of local or statewide Cooperative Extension personnel. If the herbicide application method is ruled out as the cause of poor weed control , researchers often conduct field or greenhouse tests to verify and quantify the level of resistance. Plants from the suspected herbicide-resistant population are treated with the herbicide of interest at rates ranging from below normal doses to doses well above those legally allowed in the field . The response of the putative resistant population is then compared with the response of the known susceptible, or wild-type, population. Resistance is confirmed if the herbicide affects the two populations of the same species in markedly different ways with respect to plant growth and survival. In many cases, an estimate of the level of resistance also is made from these data. For example, if the susceptible population is controlled at one-half the field rate, but the resistant population survives at twice the field rate, it would be described as having a fourfold level of resistance. Physiology and mechanisms of herbicide resistance. Identifying and verifying herbicide resistance and developing alternative management strategies provides short-term solutions for weed managers. Researchers often conduct further studies to determine the underlying molecular and physiological causes of resistance and to compare the biology, growth and competitive ability of herbicide-resistant species and biotypes. The mechanism and fitness costs of herbicide resistance can have important ramifications on the selection, spread and competitive ability of herbicide-resistant biotypes, in addition to directly impacting their management. The goal of these efforts is to help growers and pest control advisers recognize the importance of taking a proactive approach to preventing the evolution of a resistant population, rather than a reactive approach to managing herbicide resistance after it occurs. Target-site resistance occurs when the enzyme that is the target of the herbicide becomes less sensitive, or fully insensitive, to the herbicide, often due to a physical change in the target enzyme’s structure. These physical changes can impair the ability of the herbicide to attach to a specific binding site on the enzyme, thus reducing or eliminating herbicidal activity. Target-site resistance is sometimes evaluated at the tissue level using portions of plants such as leaves, leaf disks or roots . In some cases, a functioning target enzyme can be extracted and its function evaluated in laboratory in vitro experiments in the presence or absence of the herbicide. Recently, overproduction or enhanced activity of the target enzyme has been shown to confer herbicide resistance in certain cases . Several mechanisms of non-target-site resistance confer resistance to herbicides in plants without involving the target sites of the herbicides. This can result in unpredictable resistance to unrelated herbicides . Of these, the best-known cases involve resistance in which herbicide-resistant plants have an enhanced ability to metabolically degrade the herbicide to less- ornontoxic forms. Many processes can be involved in metabolic resistance, but the most well-understood cases are due to changes in three groups of isozymes and changes in ATP-binding cassette transporters . This type of resistance is most commonly evaluated using nonherbicidal inhibitors of the various isozymes in the presence or absence of the herbicide and comparing metabolic degradation of the herbicide in laboratory or greenhouse assays. Biology, ecology and evolution of herbicide resistance. 

The use of short-residual herbicides also reduces selection pressure for herbicide resistance. In addition, tank-mixing of herbicides with different modes of action can inhibit the evolution of resistance, but the combinations used should broaden the spectrum of weeds controlled along with controlling the weed species of major concern. If two herbicides have nearly the same weed control spectrum, you would do better to rotate between them rather than tank-mix the two compounds; little additional control will be achieved by adding the second material. Though unlikely, it is possible in theory that a weed population will simultaneously be selected for resistance to both herbicides. While weeds have traits that enhance their potential to evolve resistance, they also have traits that reduce that potential. Weed species with seeds that remain dormant in the soil for several years will maintain a population of susceptible plants within the seed bank. By maintaining susceptible plants in the population, a grower can dilute the resistance trait. If there is a fitness cost to resistance, removing the herbicide at some point in the crop rotation cycle will allow competition between the resistant and susceptible plants, further diluting the gene pool for the resistance trait. Besides the practice of crop rotation, certified seed, equipment sanitation, cultivation, and hand-weeding all impede resistance evolution. Resistance problems usually go undetected until land managers or farmers observe about 30 percent weed control failure for a particular species. If you can identify these resistant weed patches early, curing marijuana before their populations increase, you can employ management practices that prevent their spread.

If weed escapes appear in patterns such as distinct strips, or if several species normally controlled by the herbicide are present in these strips, the problem probably is associated with a calibration or application error. However, patches made up of only one escaped species and showing no distinctive pattern may indicate a herbicide-resistant population. Suspicious areas should be brought to the attention of a Farm Advisor or Extension Specialist, especially if weed populations reoccur in subsequent years after use of the same herbicide.However, weed species shifts and the selection for glyphosate-resistant weeds can result from the increased use of this technology if the crop is not managed properly from the outset. Aspects of the alfalfa production system both favor and discourage the occurrence of weed shifts and the evolution of resistant weeds. Alfalfa is a competitive perennial crop that is cut multiple times per year, making it difficult for most weeds to become established. On the other hand, the RR alfalfa system may be vulnerable to weed shifts and resistant weeds for several reasons: tillage typically only occurs between crops, alfalfa is produced over a wide geographical area and in large fields with a great diversity of weeds, and there is potential for long-term repeated use of a single herbicide because it is a perennial crop. In this publication we recommend an integrated weed management system designed to prevent the proliferation of tolerant or resistant weeds. Elements include crop rotation, rotations with herbicides of different modes of action , tank mixtures, and irrigation and harvest timing. Successful adaptation of these concepts into production systems would assure the long-term effectiveness and sustainability of the Roundup Ready system in alfalfa.

A preemptive approach is warranted; these strategies should be employed before weed shifts and weed resistance occur.Alfalfa, the queen of forages, is the principal forage crop in the United States and frequently the third most important crop in value. It is a vital component of the feed ration for dairy cows and is a principal feed for horses, beef cattle, sheep, and other livestock. Because animal performance depends upon the palatability and nutritional value of alfalfa, livestock managers, especially those in the dairy and horse industry, expect high-quality hay. Although many factors influence quality, the presence of grassy and broadleaf weeds plays a significant role in reducing the feeding value of hay throughout the United States. Weeds that accumulate nitrates or are poisonous to livestock are also a major concern in alfalfa, since poisonous weeds sicken or kill animals every year . Most livestock producers demand weed-free alfalfa for optimum quality and maximum animal performance. Weed-free alfalfa can be difficult to achieve, whether using non-chemical methods or conventional herbicides. Typically, no single herbicide controls all weeds present in a field, and some weeds—especially perennials—are not adequately controlled with any of the currently registered conventional herbicides. Cultural practices such as modifying harvest schedules, grazing, time of planting, and use of nurse crops such as oats help suppress weeds; however, these practices are almost never entirely effective and some of them suppress alfalfa seedling growth. In addition to being difficult to achieve, complete weed control in alfalfa is costly. Alfalfa growers continually seek ways to enhance the level of weed control while minimizing costs.Glyphosate is generally considered the most effective broad spectrum post-emergence herbicide available. The first commercially available glyphosate-resistant crops were soybean, canola, cotton, and corn, which were released in 1996, 1997, 1997, and 1998, respectively. Glyphosate-resistant or Roundup Ready alfalfa was developed through biotechnology in late 1997 and became commercially available in the fall of 2005.

This technology imparts genetic resistance to glyphosate by inserting a single gene from a soil bacterium into alfalfa. These biotechnology-derived alfalfa plants have an altered enzyme that allows them to tolerate a glyphosate application while susceptible weeds are killed. Glyphosate resistance is the first commercially available, genetically engineered trait in alfalfa. This technology was a major development in alfalfa weed control, providing growers with a useful weed management tool and a means to deal with some of the most difficult-to-control weed species. Researchers have evaluated its effectiveness as a weed control strategy . The advantages and disadvantages of this technology have been reviewed . Glyphosate was found to be especially effective for weed control in seeding alfalfa . Glyphosate typically causes no perceptible crop injury, is much more flexible and less restrictive in application, and provides superior weed control across a range of weed species when compared with other currently used herbicides. One of the greatest advantages of this technology is that it provides a tool for suppressing perennial weeds such as dandelion , yellow nutsedge , bermudagrass Pers., and quackgrass Nevski that have not been adequately controlled with conventional practices. After deregulation of this trait in 2005, over 300,000 acres of RR alfalfa were planted in the United States, about 1.4 percent of U.S. acreage. However, in the spring of 2007, further plantings were suspended pending the outcome of a legal challenge and further environmental analysis by the U.S. Department of Agriculture’s Animal and Plant Health Inspection Service . There were two key issues in this process: the possibility of contamination of organic and conventional alfalfa through the adventitious presence of the gene, and the possibility of a greater level of weed resistance due to the adoption of the Roundup Ready technology in alfalfa . Grower experience in commercial fields following deregulation confirmed many of the benefits that early research had suggested in terms of the efficacy and safety of the RR system . Growers have generally found that this technology is easy to use and provides superior weed control and improved forage quality in many cases compared with conventional herbicides. However, no new technology is a panacea, and, pipp mobile storage like other weed control strategies, RR alfalfa has its limitations. An important limitation of this new weed-management system is the potential for weed shifts and weed resistance. This publication discusses techniques that are available to manage the possibility of weed shifts and weed resistance occurring in Roundup Ready alfalfa weed control systems.Change in weed populations as a result of repeated use of a single herbicide is not a new phenomenon. Such changes result from shifts in the weeds present from susceptible to tolerant species, or conversion of a population within a species to resistant individuals, as a consequence of selection pressure .In the case of chemical weed control, no single herbicide controls all weeds, as weeds differ in their susceptibility to an herbicide. This allows inherently tolerant weed species to remain, which often thrive and proliferate with the reduced competition. As a result, there is a gradual shift to tolerant weed species when practices are continuously used that are not effective against those species.

A weed shift does not necessarily have to be a shift to a different species. For example, with a foliar herbicide without residual activity like glyphosate, there could also be a shift within a weed species to a late-emerging biotype that emerges after application. In the case of weed shifts, the total population of weeds does not necessarily change as a result of an herbicide or an agronomic practice; these practices simply favor one species over another.In contrast to a weed shift, weed resistance is a change in the population of weeds that were previously susceptible to an herbicide, turning them into a population of the same species that is no longer controlled by that herbicide .While weed shifts can occur with any agronomic practice , the evolution of weed resistance is only the result of continued herbicide application. The use of a single class of herbicides continually over time creates selection pressure so that resistant individuals of a species survive and reproduce, while susceptible ones are killed.A weed species shift is far more common than weed resistance, and ordinarily takes less time to develop. If an herbicide does not control all the weeds, the tendency is to quickly jump to the conclusion that resistance has occurred. However, a weed shift is a far more likely explanation for weed escapes following an application of glyphosate. See table 1 for a list of weeds sometimes found in alfalfa fields that are tolerant to or difficult to control with glyphosate.A common misconception is that weed resistance is intrinsically linked to genetically engineered crops. However, this is not correct. The occurrence of weed shifts and weed resistance is not unique to genetically engineered crops. Weed shifts and resistance are caused by the practices that may accompany a GE crop , not the GE crop itself. Similarly, some people believe that herbicide resistance is transferred from the GE crop to weed species. However, unless a crop is genetically very closely related to a naturally-occurring weed, weed resistance cannot be transferred from crop to weed. In the case of alfalfa, there are no known wild plants that cross with alfalfa, so direct transfer of herbicide resistance through gene flow to weedy species will not occur. However, the glyphosate-tolerant genes from RR alfalfa can be transferred to feral alfalfa plants if cross pollination occurs.resistance is transferred from the GE crop to weed species. However, unless a crop is genetically very closely related to a naturally-occurring weed, weed resistance cannot be transferred from crop to weed. In the case of alfalfa, there are no known wild plants that cross with alfalfa, so direct transfer of herbicide resistance through gene flow to weedy species will not occur. However, the glyphosate-tolerant genes from RR alfalfa can be transferred to feral alfalfa plants if cross pollination occurs.Transgenic herbicide-resistant crops do, nonetheless, have greater potential to foster weed shifts and resistant weeds since a grower is more likely to use a single herbicide repeatedly in herbicide-resistant crops such as RR alfalfa. Additionally, the accumulation of acreage of different RR crops could increase the potential for weed shifts or weed resistance in cropping systems utilizing RR crops. This is because the probability of repeated use of the same herbicide is higher and the potential applied acreage is greater. Fortunately, there are simple methods available to prevent weed shifts and weed resistance from occurring. In studies conducted in San Joaquin County, California, weeds shifts were found to occur during the first few years of use when glyphosate-tolerant weeds were present . Annual bluegrass and shepherd’s purse were adequately controlled with glyphosate, whereas chickweed control was about 80 percent and burning nettle andannual sowthistle were not adequately controlled with any of the glyphosate rates . During the 3 years of this field trial, when glyphosate was used repeatedly, there was a gradual weed species shift away from annual bluegrass and shepherd’s purse to higher populations of burning nettle and annual sowthistle .

Intriguing differeIntriguing differentially expressed genes located within likelihood intervals of rhizome related quantitative trait loci include an auxilin/cyclin G-associated kinase , tandemly duplicated ethylene responsive transcription factors , and a Ca2 + /calmodulindependent protein kinase, EF-Hand protein superfamily gene . Both polyploidy and interspecific hybridity appear to contribute to the ‘mosaic’ nature of rhizome gene expression, with over expression of some homoeologs from rhizomatous S. propinquum and others from non-rhizomatous S. bicolor . For example, different calmodulin family members have evolved specificity to rhizome buds and shoot buds . Tandem duplicated ethylene responsive transcription factors within a rhizome-related QTL are both overexpressed in S. halepense rhizome buds, although the sequence of Sb07g006195 closely resembles S. propinquum and adjacent Sb07g006200 is identical to S. bicolor . The Teosinte-branched 1 growth repressor gene implicated in apical dominance of maize shoots has two family members with enriched expression in rhizome buds , ironically both completely matching the non-rhizomatous S. bicolor progenitor sequences .Introgression is suggested in a general sense by S. bicolor enriched allele composition of the S. halepense draft genome , and for specific genes by S. halepense SNP distribution patterns matching the S. bicolor reference genome of an elite breeding line , but differing from both several wild S. bicolors and each of two outgroups . Seven ‘hotspots’ for introgression of sorghum alleles in five geographically diverse US S. halepense populations , show non-random correspondence with published sorghum QTLs conferring variation in rhizome growth, curing cannabis seed size, and lutein content . While sorghum lacks rhizomes and has large seeds, rhizome growth-related alleles masked in domesticated sorghum genotypes by a lack of rhizomes may be unmasked in interspecific crosses with rhizomatous S. halepense.

Particularly intriguing among S. halepense introgression hotspots are those that correspond with 3 of 4 QTL likelihood intervals spanning 4.9% of the genome that account for variation in seed content of the carotenoid lutein . Sorghum leaf photosynthetic capacity is susceptible to damage under low-temperature but high-light conditions when electron transport exceeds the capacity of carbon fixation to utilize available energy . Such conditions are infrequent in the tropics where Sorghum originated but common in the temperate springtime. Spring regrowth of S. halepense starts about 4 weeks before cultivated sorghum is seeded at 38.7◦ N . Xanthophyll carotenoids such as lutein are most abundant in plant leaves, modulating light energy and performing non-photochemical quenching of excited ‘triplet’ chlorophyll which is overproduced at very high light levels during photosynthesis . Ironically, Sb01g030050 and Sb01g048860 related to lutein biosynthesis, are close to the only lutein QTL not near an introgression hotspot . Within the lutein QTL likelihood intervals, and homozygous in the Gypsum 9E , are also loss of function mutations in Sb01g013520, 9-cis epoxycarotenoid dioxygenase. This enzyme cleaves xanthophylls to xanthoxin, a precursor of the plant hormone abscisic acid  that plays a central role in regulating plant tissue quiescence. Also in the lutein QTL likelihood intervals are nonsynonymous SNPs inferred to have striking functional effects on Sb02g026600, a cytochrome P450 performing a key step of ABA catabolism . A hypothesis for investigation is whether modified alleles at these loci degrade ABA to release S. halepense seeds from dormancy early and/or increase seedling vigor under cold conditions.Synergy between gene duplication and interspecific hybridity may add an important element to the classical notion that polyploids adapt better than their diploid progenitors to environmental extremes .

Evidence is growing that polyploidy is an important contributor to biological invasions . Genome duplication facilitates the evolution of genes with new or modified functions such as we report, permitting a nascent polyploid to adapt to environments beyond the reach of its progenitors. Hybridity preserves novel alleles such as many recruited into S. halepense rhizome-enriched gene expression from non-rhizomatous S. bicolor, putatively contributing to the transgressive rhizome growth and ability of S. halepense but not rhizomatous S. propinquum derived progeny to overwinter in the temperate United States. Several lines of evidence point to a richness of DNA-level variation in S. halepense, including an abundance of novel coding sequences, much richer diversity of neutral DNA markers than its progenitors, and novel gene expression patterns exemplified by rhizome-enriched expression of some alleles from its nonrhizomatous S. bicolor progenitor. The spread of invasive taxa is much more rapid than migration in native taxa, and may require more genetic variation to sustain . Although there is somewhat less variation near the invasion front than the center of its US distribution , rich S. halepense diversity may support its projected 200–600 km northward spread in the coming century . Rich genetic variation in S. halepense offers not only challenges but also opportunities. Long under selection for weediness related attributes that enhance its competitiveness with crops, some US S. halepense genotypes have transitioned to nonagricultural niches and may also experience selection favoring alleles that could improve sorghum and other crops, e.g., for cold tolerance, rapid vegetative development and flowering, disease and pest resistance, and ratooning . Sorghum bicolor can routinely serve as the pollen parent of triploid and tetraploid and under some circumstances diploid , interspecific hybrids with Sh, offering the opportunity to test S. halepense alleles in sorghum.

As the first surviving polyploid in its lineage in ∼96 million years , S. halepense may open new doors to sorghum improvement, with synergy between gene duplication and interspecific hybridity nurturing the evolution of genes with new or modified functions . Already, genetic novelty from S. halepense is being used in efforts to breed ratooning/perennial sorghums that better protect ‘ecological capital’ such as topsoil and organic matter . Attributes of S. halepensesuch as endophytic nitrogen fixation , if transferred to sorghum, could help to narrow a ‘yield gap’ reflected by 1961–2012 yield gains in the U.S. of only 61% for sorghum versus 323% for maize2 . Likewise, its perenniality may have resulted in selection for ‘durable’ biotic stress resistance mechanisms that are absent from, but of importance to the improvement of, sorghum and other crops.The temperate region summer annual weed EchinochloaoryzicolaVasing. is a morphological mimic of rice that can germinate and initiate shoot growth under hypoxia in flooded paddies and causes up to 50% rice yield losses in California if not controlled. Decades of heavy reliance on herbicides for E. oryzicola control have resulted in the widespread occurrence of populations with simultaneous resistance to most available grass herbicides for selective use in rice.Successful control of herbicide-resistant E. oryzicola now hinges on maximizing weed seedling recruitment in order to eliminate such seedlings prior to planting the crop.The stale seedbed approach entails recruiting and treating weeds prior to planting rice with a mechanical method or a broad spectrum herbicide for which resistance does not exist in these weeds. The effectiveness of this approach would be optimized if the timing of weed seedling emergence under varying temperatures and irrigation regimes could be accurately predicted and if the conditions for maximizing emergence rate and synchrony could be identified. Population-based threshold models have been developed to describe germination responses to temperature, water potential and oxygen, and have been used to predict crop seedling emergence. For non-dormant E. oryzicola seed, the PBTM approach predicted with useful accuracy the germination responses of seeds to shifting temperature and water availability and their subsequent emergence from field soils. However, Poaceae seeds typically possess non-deep physiological dormancy , which indicates that seed dormancy release and increases in germination rates vary along a continuum of time and environmental conditions. NDPD may be released by stratification, after-ripening, scarification, excision of the embryo or addition of gibberellin and by various environmental signals including light, fluctuating temperatures and soil nitrate. In addition, the environmental requirements for dormancy alleviation are often population- rather than species specific, thus requiring analysis at the population level. While non-dormant seeds of selected herbicide-resistant and herbicide-susceptible populations of E. oryzicola germinated similarly, information on differences in seed dormancy between R and S populations is lacking. Herbicide-resistant E.oryzicola populations trace their origin to a single introduced biotype dispersed throughout California rice fields suggesting that R populations may respond similarly to environmental variables affecting germination and dormancy. As in many summer annual species with NDPD, innate dormancy of E. oryzicola seed populations that emerge in spring is alleviated by cold stratification when exposed to a period of moisture at wintertime temperatures in California. Thus,hydration and dark storage at 3uC alleviated dormancy of most seeds in this species. In California, yearly wintertime variation in field temperatures may be less than year-to-year variation in moisture levels, which may range from sporadic rain to prolonged periods of flooding. Adaptation to these conditions would suggest that stratification moisture levels may influence the magnitude of E. oryzicola seed dormancy release and that dormancy levels could perhaps be manipulated using wintertime irrigation to increase the rate of springtime germination and weed seedling recruitment. The median base water potential estimated using hydrotime germination models is often a measure of the relative dormancy status of a seed population, and because dormancy removal enables E. oryzicola seeds to transition from aerobic respiration to anaerobic alcoholic fermentation, oxygen-time germination models might also provide a means of assessing dormancy levels in seeds of this species. To understand the environmental requirements for E. oryzicola seed dormancy alleviation, we sought here to: 1) quantify stratification effects upon germination of seeds of R and S populations of E. Oryzicola across a range of moisture and oxygen levels; and 2) ascertain the relative contributions of alternating temperatures and of stratification temperature, water potential and duration towards dormancy release in R and S E. oryzicola populations. This knowledge will contribute towards the accuracy of germination-based predictions of seedling emergence as affected by the dormancy status of the seed and thus improve the timing and efficacy of weed control programs.E. oryzicola seeds of four populations representing the range of phenotypic variability previously reported in California were mass collected from Sacramento Valley, California, rice fields between 1997 and 2002 [16] and used in all experiments of this study. Populations CR and HR were subsequently classified as herbicide-susceptible and populations KS and SW as herbicide-resistant. In the summers of 2007 and 2009, 38 plants from each population were placed in separate greenhouses for seed multiplication at the University of California, Davis. Plants were grown in 2-L pots filled with soil placed in flooded basins under conditions set to approximate mid-springtime field conditions in the Sacramento Valley: 28/14uC day/ night temperatures, 50% relative humidity;natural light was supplemented by 900 mmol m22 s 21 of photosynthetic photon flux density from metal halide and high pressure sodium lamps to maintain a 16-h day length; soluble fertilizer was applied through irrigation as needed. Seeds were harvested from panicles at the time of seed shattering in early fall, stored at 20uC for 3 weeks to approximate typical early autumn temperatures and thereafter stored at 3uC, approximating mid-winter temperatures. Water content of seeds kept in dry storage was 7 to 9% .Tillage has long been an essential component of traditional agricultural systems. Broadly defined, tillage is the mechanical manipulation of the soil and plant residues to prepare a seedbed for crop planting. The benefits of tillage are many: it loosens soil, enhances the release of nutrients from the soil for crop growth, kills weeds, and regulates the circulation of water and air within the soil . In some cases, however, intensive tillage has been found to adversely affect soil structure and cause excessive breakdown of aggregates, leading to soil erosion in higher-rainfall areas. Intensive tillage can also have a negative impact on environmental quality by accelerating soil carbon loss and greenhouse gas emissions . Further, tillage operations account for more than 25 percent of agricultural production costs . With recent increases in fuel prices, tillage now accounts for a higher proportion of production costs than harvesting does . Such concerns have fueled interest in finding tillage systems that minimize negative impacts to the environment while sustaining economic crop productivity. The tillage systems being developed and studied to address these concerns can broadly be termed conservation tillage . In California, conventional tillage practices face additional challenges as population centers expand into farming areas and new residents raise serious concerns about the air quality effects of smog and dust emissions from farm machinery and vehicle use. Growers in California are looking at CT as a possible way to reduce their operating costs. Estimates from the Conservation Technology Information Center showed that by switching to CT, a U.S. grower can save as much as 225 labor hours and 1750 gallons of fuel per year on just 500 acres.ntially expressed genes located within likelihood intervals of rhizome related quantitative trait loci include an auxilin/cyclin G-associated kinase , tandemly duplicated ethylene responsive transcription factors , and a Ca2 + /calmodulindependent protein kinase, EF-Hand protein superfamily gene . Both polyploidy and interspecific hybridity appear to contribute to the ‘mosaic’ nature of rhizome gene expression, with over expression of some homoeologs from rhizomatous S. propinquum and others from non-rhizomatous S. bicolor . For example, different calmodulin family members have evolved specificity to rhizome buds and shoot buds . Tandem duplicated ethylene responsive transcription factors within a rhizome-related QTL are both overexpressed in S. halepense rhizome buds, although the sequence of Sb07g006195 closely resembles S. propinquum and adjacent Sb07g006200 is identical to S. bicolor .

The Teosinte-branched 1 growth repressor gene implicated in apical dominance of maize shoots has two family members with enriched expression in rhizome buds , ironically both completely matching the non-rhizomatous S. bicolor progenitor sequences .Introgression is suggested in a general sense by S. bicolor enriched allele composition of the S. halepense draft genome , and for specific genes by S. halepense SNP distribution patterns matching the S. bicolor reference genome of an elite breeding line , but differing from both several wild S. bicolors and each of two outgroups . Seven ‘hotspots’ for introgression of sorghum alleles in five geographically diverse US S. halepense populations , show non-random correspondence with published sorghum QTLs conferring variation in rhizome growth, seed size, and lutein content . While sorghum lacks rhizomes and has large seeds, rhizome growth-related alleles masked in domesticated sorghum genotypes by a lack of rhizomes may be unmasked in interspecific crosses with rhizomatous S. halepense. Particularly intriguing among S. halepense introgression hotspots are those that correspond with 3 of 4 QTL likelihood intervals spanning 4.9% of the genome that account for variation in seed content of the carotenoid lutein . Sorghum leaf photosynthetic capacity is susceptible to damage under low-temperature but high-light conditions when electron transport exceeds the capacity of carbon fixation to utilize available energy . Such conditions are infrequent in the tropics where Sorghum originated but common in the temperate springtime. Spring regrowth of S. halepense starts about 4 weeks before cultivated sorghum is seeded at 38.7◦ N . Xanthophyll carotenoids such as lutein are most abundant in plant leaves, weed dryer modulating light energy and performing non-photochemical quenching of excited ‘triplet’ chlorophyll which is overproduced at very high light levels during photosynthesis . Ironically, Sb01g030050 and Sb01g048860 related to lutein biosynthesis, are close to the only lutein QTL not near an introgression hotspot . Within the lutein QTL likelihood intervals, and homozygous in the Gypsum 9E , are also loss of function mutations in Sb01g013520, 9-cis epoxycarotenoid dioxygenase. This enzyme cleaves xanthophylls to xanthoxin, a precursor of the plant hormone abscisic acid  that plays a central role in regulating plant tissue quiescence. Also in the lutein QTL likelihood intervals are nonsynonymous SNPs inferred to have striking functional effects on Sb02g026600, a cytochrome P450 performing a key step of ABA catabolism . A hypothesis for investigation is whether modified alleles at these loci degrade ABA to release S. halepense seeds from dormancy early and/or increase seedling vigor under cold conditions.Synergy between gene duplication and interspecific hybridity may add an important element to the classical notion that polyploids adapt better than their diploid progenitors to environmental extremes . Genome duplication facilitates the evolution of genes with new or modified functions such as we report, permitting a nascent polyploid to adapt to environments beyond the reach of its progenitors. Hybridity preserves novel alleles such as many recruited into S. halepense rhizome-enriched gene expression from non-rhizomatous S. bicolor, putatively contributing to the transgressive rhizome growth and ability of S. halepense but not rhizomatous S. propinquum derived progeny to overwinter in the temperate United States. Several lines of evidence point to a richness of DNA-level variation in S. halepense, including an abundance of novel coding sequences, much richer diversity of neutral DNA markers than its progenitors, and novel gene expression patterns exemplified by rhizome-enriched expression of some alleles from its nonrhizomatous S. bicolor progenitor. The spread of invasive taxa is much more rapid than migration in native taxa, and may require more genetic variation to sustain . Although there is somewhat less variation near the invasion front than the center of its US distribution , rich S. halepense diversity may support its projected 200–600 km northward spread in the coming century . Rich genetic variation in S. halepense offers not only challenges but also opportunities. Long under selection for weediness related attributes that enhance its competitiveness with crops, some US S. halepense genotypes have transitioned to nonagricultural niches and may also experience selection favoring alleles that could improve sorghum and other crops, e.g., for cold tolerance, rapid vegetative development and flowering, disease and pest resistance, and ratooning . Sorghum bicolor can routinely serve as the pollen parent of triploid and tetraploid and under some circumstances diploid , interspecific hybrids with Sh, offering the opportunity to test S. halepense alleles in sorghum. As the first surviving polyploid in its lineage in ∼96 million years , S. halepense may open new doors to sorghum improvement, with synergy between gene duplication and interspecific hybridity nurturing the evolution of genes with new or modified functions . Already, genetic novelty from S. halepense is being used in efforts to breed ratooning/perennial sorghums that better protect ‘ecological capital’ such as topsoil and organic matter . Attributes of S. halepensesuch as endophytic nitrogen fixation , if transferred to sorghum, could help to narrow a ‘yield gap’ reflected by 1961–2012 yield gains in the U.S. of only 61% for sorghum versus 323% for maize2 . Likewise, its perenniality may have resulted in selection for ‘durable’ biotic stress resistance mechanisms that are absent from, but of importance to the improvement of, sorghum and other crops.The temperate region summer annual weed EchinochloaoryzicolaVasing. is a morphological mimic of rice that can germinate and initiate shoot growth under hypoxia in flooded paddies and causes up to 50% rice yield losses in California if not controlled. Decades of heavy reliance on herbicides for E. oryzicola control have resulted in the widespread occurrence of populations with simultaneous resistance to most available grass herbicides for selective use in rice.Successful control of herbicide-resistant E. oryzicola now hinges on maximizing weed seedling recruitment in order to eliminate such seedlings prior to planting the crop.The stale seedbed approach entails recruiting and treating weeds prior to planting rice with a mechanical method or a broad spectrum herbicide for which resistance does not exist in these weeds. The effectiveness of this approach would be optimized if the timing of weed seedling emergence under varying temperatures and irrigation regimes could be accurately predicted and if the conditions for maximizing emergence rate and synchrony could be identified. Population-based threshold models have been developed to describe germination responses to temperature, water potential and oxygen, and have been used to predict crop seedling emergence. For non-dormant E. oryzicola seed, the PBTM approach predicted with useful accuracy the germination responses of seeds to shifting temperature and water availability and their subsequent emergence from field soils. However, Poaceae seeds typically possess non-deep physiological dormancy , which indicates that seed dormancy release and increases in germination rates vary along a continuum of time and environmental conditions. NDPD may be released by stratification, after-ripening, scarification, excision of the embryo or addition of gibberellin and by various environmental signals including light, fluctuating temperatures and soil nitrate. In addition, the environmental requirements for dormancy alleviation are often population- rather than species specific, thus requiring analysis at the population level. While non-dormant seeds of selected herbicide-resistant and herbicide-susceptible populations of E. oryzicola germinated similarly, information on differences in seed dormancy between R and S populations is lacking. Herbicide-resistant E.oryzicola populations trace their origin to a single introduced biotype dispersed throughout California rice fields suggesting that R populations may respond similarly to environmental variables affecting germination and dormancy. As in many summer annual species with NDPD, innate dormancy of E. oryzicola seed populations that emerge in spring is alleviated by cold stratification when exposed to a period of moisture at wintertime temperatures in California. Thus,hydration and dark storage at 3uC alleviated dormancy of most seeds in this species. In California, yearly wintertime variation in field temperatures may be less than year-to-year variation in moisture levels, which may range from sporadic rain to prolonged periods of flooding. Adaptation to these conditions would suggest that stratification moisture levels may influence the magnitude of E. oryzicola seed dormancy release and that dormancy levels could perhaps be manipulated using wintertime irrigation to increase the rate of springtime germination and weed seedling recruitment. The median base water potential estimated using hydrotime germination models is often a measure of the relative dormancy status of a seed population, and because dormancy removal enables E. oryzicola seeds to transition from aerobic respiration to anaerobic alcoholic fermentation, oxygen-time germination models might also provide a means of assessing dormancy levels in seeds of this species. To understand the environmental requirements for E. oryzicola seed dormancy alleviation, we sought here to: 1) quantify stratification effects upon germination of seeds of R and S populations of E. Oryzicola across a range of moisture and oxygen levels; and 2) ascertain the relative contributions of alternating temperatures and of stratification temperature, water potential and duration towards dormancy release in R and S E. oryzicola populations. This knowledge will contribute towards the accuracy of germination-based predictions of seedling emergence as affected by the dormancy status of the seed and thus improve the timing and efficacy of weed control programs.E. oryzicola seeds of four populations representing the range of phenotypic variability previously reported in California were mass collected from Sacramento Valley, California, rice fields between 1997 and 2002 [16] and used in all experiments of this study. Populations CR and HR were subsequently classified as herbicide-susceptible and populations KS and SW as herbicide-resistant. In the summers of 2007 and 2009, 38 plants from each population were placed in separate greenhouses for seed multiplication at the University of California, Davis. Plants were grown in 2-L pots filled with soil placed in flooded basins under conditions set to approximate mid-springtime field conditions in the Sacramento Valley: 28/14uC day/ night temperatures, 50% relative humidity;natural light was supplemented by 900 mmol m22 s 21 of photosynthetic photon flux density from metal halide and high pressure sodium lamps to maintain a 16-h day length; soluble fertilizer was applied through irrigation as needed. Seeds were harvested from panicles at the time of seed shattering in early fall, stored at 20uC for 3 weeks to approximate typical early autumn temperatures and thereafter stored at 3uC, approximating mid-winter temperatures. Water content of seeds kept in dry storage was 7 to 9% .Tillage has long been an essential component of traditional agricultural systems. Broadly defined, tillage is the mechanical manipulation of the soil and plant residues to prepare a seedbed for crop planting. The benefits of tillage are many: it loosens soil, enhances the release of nutrients from the soil for crop growth, kills weeds, and regulates the circulation of water and air within the soil . In some cases, however, intensive tillage has been found to adversely affect soil structure and cause excessive breakdown of aggregates, leading to soil erosion in higher-rainfall areas. Intensive tillage can also have a negative impact on environmental quality by accelerating soil carbon loss and greenhouse gas emissions . Further, tillage operations account for more than 25 percent of agricultural production costs . With recent increases in fuel prices, tillage now accounts for a higher proportion of production costs than harvesting does . Such concerns have fueled interest in finding tillage systems that minimize negative impacts to the environment while sustaining economic crop productivity. The tillage systems being developed and studied to address these concerns can broadly be termed conservation tillage . In California, conventional tillage practices face additional challenges as population centers expand into farming areas and new residents raise serious concerns about the air quality effects of smog and dust emissions from farm machinery and vehicle use. Growers in California are looking at CT as a possible way to reduce their operating costs. Estimates from the Conservation Technology Information Center showed that by switching to CT, a U.S. grower can save as much as 225 labor hours and 1750 gallons of fuel per year on just 500 acres.

Once isolated, high-value unknowns can then be synthesized to determine their direct biological activities and mobility. Additionally, they can be more finely monitored to discern their spatial distributions. There will be several translational opportunities stemming from these efforts. Biosynthetic pathways could be engineered to produce new bioactive metabolites into plants or other organisms; these could be useful beyond plant health applications. Furthermore, for pathogen/pest-derived chemicals, a next step will be to develop strategies such as HIGS to abrogate pest/microbe chemical effectors. As noted above, chemical immunomodulators could be applied in the field or plants with altered chemistry could be bred/engineered as part of a disease control strategy. Knowledge of the chemical repertoires of plants and their associated microbes/pests could allow the design of sensitive metabolite biosensors that would act as sentinels for perturbations.Diverse pathogens, pests, parasites, and symbionts deploy large repertoires of secreted proteins known as effectors to modify host processes for their benefit. Effector activities range from the suppression of plant immunity to the manipulation of host biochemical and developmental processes. In addition to these virulence activities, effectors can trigger immunity following recognition by cognate receptors, often NLR proteins . Effectors are thus central in dictating the outcomes of plant immunity and disease development. Comprehensive characterization of effector repertoires and determination of their modes of action should therefore be a high priority. Understanding effector biology offers several opportunities for disease control, pipp horticulture as well as tools for manipulating plant biochemistry and development in the absence of disease. Effectors that trigger immunity can expedite the discovery of R genes .

Selection of breeding material with individual effectors is an informative alternative to marker-assisted selection that can facilitate pyramiding multiple R genes, each of which confers resistance to most or all strains of a pathogen by allowing selection of each R gene individually. Effectors have been effectively used in resistance breeding to control diseases caused by diverse classes of pathogen . Effector directed breeding also provides the possibility of identifying and prioritizing R genes that recognize core effectors that are broadly conserved within the species and play important roles in virulence. R genes that recognize core effectors are potentially more durable to pathogen co-evolution, because deletion or silencing of the effector would impose a fitness penalty on the pathogen; however, the caveats regarding possible second site compensating mutations and redundancy in effector function need to be considered . In addition, effector-based screens can be used to identify sources of resistance in plants that are non-hosts for the pathogen of interest. Effectors are also needed for comparative functional studies of the biophysical/biochemical basis of immune-receptor activation . This will address how many ways there are to activate NLRs and how receptor complexes are impacted biochemically and biophysically by immune modulating effectors. Having this information will provide opportunities to re-wire activation mechanisms to facilitate resistance.Diverse pathogens, pests, parasites, and symbionts deploy large repertoires of secreted proteins known as effectors to modify host processes for their benefit. Effector activities range from the suppression of plant immunity to the manipulation of host biochemical and developmental processes.

In addition to these virulence activities, effectors can trigger immunity following recognition by cognate receptors, often NLR proteins . Effectors are thus central in dictating the outcomes of plant immunity and disease development. Comprehensive characterization of effector repertoires and determination of their modes of action should therefore be a high priority. Understanding effector biology offers several opportunities for disease control, as well as tools for manipulating plant biochemistry and development in the absence of disease. Effectors that trigger immunity can expedite the discovery of R genes . Selection of breeding material with individual effectors is an informative alternative to marker-assisted selection that can facilitate pyramiding multiple R genes, each of which confers resistance to most or all strains of a pathogen by allowing selection of each R gene individually. Effectors have been effectively used in resistance breeding to control diseases caused by diverse classes of pathogen . Effector directed breeding also provides the possibility of identifying and prioritizing R genes that recognize core effectors that are broadly conserved within the species and play important roles in virulence. R genes that recognize core effectors are potentially more durable to pathogen co-evolution, because deletion or silencing of the effector would impose a fitness penalty on the pathogen; however, the caveats regarding possible second site compensating mutations and redundancy in effector function need to be considered . In addition, effector-based screens can be used to identify sources of resistance in plants that are non-hosts for the pathogen of interest. Effectors are also needed for comparative functional studies of the biophysical/biochemical basis of immune-receptor activation .

This will address how many ways there are to activate NLRs and how receptor complexes are impacted biochemically and biophysically by immune modulating effectors. Having this information will provide opportunities to re-wire activation mechanisms to facilitate resistance.In addition to improving genetics of a crop itself to enhance resistance against deleterious organisms, there are multiple opportunities to use beneficial plant-associated organisms as allies . These include many types of microbes, arthropod predators and 12 / Molecular Plant-Microbe Interactionsparasitoids, companion crops, and other organisms. Beneficial microorganisms play a central role in maintaining plant health in terms of both nutrition and defense. For example, arbuscular mycorrhizal fungi and plant growth-promoting rhizobacteria not only enhance plant nutrient capture but also can directly modulate plant defenses . The advent of high throughput DNA and RNA sequencing technologies and increased capacity for characterizing small molecules from soil samples have driven a rapid expansion in environmental genomics directly germane to plant productivity . However, virtually nothing is known of the principles of evolution and biochemistries that determine the composition of plant-associated microbiota above and below ground. Robust experimental systems are crucially needed to investigate principles of microbiota structure and function, from reductionist settings, through increasingly complex ecological settings, to deployment. Most crops have been bred independently of many of their rhizosphere- and phyllosphere associated organisms, potentially due to loss of microbe diversity and intensity in agricultural ecosystems as a result of tillage and chemical inputs . Traditional breeding programs may have inadvertently selected against beneficial microbial associations due to their use of high nutrient conditions and pesticides, which decrease opportunities for microbial benefits. For example, under ample soil nutrient conditions, the carbon drain of AMF can present a fitness cost, potentially selecting against traits favoring mycorrhizal associations. Research is required to evaluate the performance of different crop genotypes under low input conditions, including their ability to attract and sustain beneficial microorganisms. There is a dearth of knowledge as to how intra- or inter-specific plant genetic variation impacts the plant-associated microbiota. Current results support the existence of a core microbiome that may be tuned by specific plant genotype x microbiome and genotype x environment interactions . For example, plant root exudates contain signaling chemicals that influence the species composition of the rhizosphere but little is known of natural genetic variation influencing the support of beneficial rhizosphere microbes. Harnessing beneficial microbes will be increasingly important as low-till, low-input agricultural systems are adopted . Foundational research is also needed to identify appropriate combinations of beneficial organisms that can be used to develop cocktails of plant growth promoting or bio-control organisms. Addressing this difficult challenge is dependent on deriving associations of microbes that provide diverse benefits to plants and are also able to invade and persist as complex microbial communities in the target environment, vertical growing weed potentially in a co-dependent manner. Research is needed to investigate trade-offs involved in hosting potentially beneficial microorganisms. Priming is a long-lasting memory that provides potentiation of faster and stronger defense responses . Beneficial microorganisms have been demonstrated to induce defense; well-studied examples include root-colonizing bacteria that promote plant growth and provide enhanced broad spectrum resistance to several types of pathogens . Pathogens can also activate resistance distant from the site of infection . Some signaling components are involved in both of these long-distance responses. The challenge is to ensure that plants have the capacity to be well-colonized with ISR-promoting microbes and also capable of adequately activating these signaling pathways for resistance.

Priming or induction of plant defenses, particularly SAR, may incur a yield penalty, which is yet to be fully understood. Germplasm should therefore be screened to find genotypes amenable to beneficial colonization. Plant genes that regulate responses to different microbial populations should also be characterized to identify input genotypes for breeding programs to enhance beneficial associations. Progress towards implementing these strategies will require extensive sequencing for microbial characterization, high resolution metabolomics, the ability to culture and maintain promising organisms, and the ability to assess many plants rapidly for a variety of responses. It is important to develop interventions for improving plant health that go beyond altering crop genetics. Small molecule signals generated in response to beneficial microorganisms could be commercialized for external application, in a similar manner to chemicals inducing SAR. Both biological control and bio-pesticides have much scope for development. There are multiple approaches to improving biological control by boosting populations of natural enemies of pests, pathogens, and weeds. Classical bio-control involves recruiting biological control agents from the areas of origin of invasive pests and weeds and introducing them to the areas where they have invaded. This approach has had several impressive successes as well as some inconsistent results. It requires long-term research efforts to find candidates, determine likely effectiveness, and verify safety. Conservation bio-control involves exploiting resident populations of natural enemies of pests, weeds and pathogens as an ecosystem service; interventions to improve the effectiveness of conservation bio-control are required to support natural populations. Again, the new tools for determining microbial community structure and identifying insect pest population structure help to build mechanistic understanding of the ecosystems, leading to more reliable predictions. This requires food resources and suitable habitat. Considerable progress has been made with field margins to support populations of natural enemies of insect pests; however, there is often insufficient movement of beneficials into the crop where they are needed. Lure and reward strategies to attract beneficials with semiochemicals coupled with food rewards that enhance their fitness and performance are required . A greater foundational understanding of the ecology of tritrophic interactions and signaling is needed to enable better recruitment of natural enemies of pests , perhaps by breeding. Companion cropping can both repel pests and attract their natural enemies; a successful example of this is the push-pull system in Kenya . The development of biopesticides involves formulation of living organisms, for example an entomopathogenic fungus or a virus that affects insects, can kill the pest target and can be sprayed or applied like a pesticide. Research priorities include discovery of new agents, development of new biopesticide delivery methods, and approaches in which a killing agent is formulated with an attractant semiochemical.Because viruses are obligate intra-cellular pathogens with small genomes, they are completely dependent on cellular host factors to complete their life cycle and on vectors such as insects, nematodes, or plasmodiophorids for dissemination. Plant viruses are comprised of either RNA or DNA genomes, which typically encode only four to ten proteins and differ in replication strategies . Several aspects of viral biology remain insufficiently characterized. The last decade has seen major advances in characterization of host factors involved in replication and movement and virus manipulation of host gene regulation . Viruses also modify host and insect vector behaviors . However, the knowledge of the underlying mechanisms is still lacking. In addition, virus-plant and virus-vector interactions as well as regulatory host small RNAs are affected by environmental factors such as temperature and light . The basis of virus specificity for certain cell types and tissues and why some viruses have wide or narrow host ranges are also not understood. It is known that hormone and defense pathways are affected by viruses, but information on spatial and temporal restriction of viruses at the cellular level is lacking. Discovery of the underlying reasons may enable the development of novel strategies that restrict virus infection. The drivers of virus evolution and the mechanisms by which vector population complexity influences viral population composition and transmission remain incompletely known. Multiple studies are needed to address these gaps in our knowledge. Single-cell genomics and transcriptional profiling may reveal molecular details of viral restriction, cell autonomous and nonautonomous virus responses, basis of seed transmission, and the influence of environmental factors and host developmental stage on virus infection. Development of anti-viral peptides targeting key components is needed to determine the basis of host and tissue specificity.

The global population is projected to reach 9.7 billion by 2050, and traditional farming methods are struggling to keep up with the rising demand for food. At the same time, urbanization and climate change are shrinking arable land, forcing innovators to rethink agriculture. Enter vertical farming and hydroponics—two technologies that promise to revolutionize food production. But can they work together? Specifically, can vertical grow racks be used for hydroponics?

This article explores the synergy between vertical grow racks and hydroponic systems, analyzing their compatibility, benefits, challenges, pipp racking and real-world applications. By the end, you’ll understand why this combination is not just possible but a game-changer for sustainable agriculture.

Section 1: Understanding Vertical Grow Racks and Hydroponics

What Are Vertical Grow Racks?

Vertical grow racks are multi-tiered structures designed to maximize growing space by stacking plants vertically. These systems are commonly made of metal or plastic and can be adjusted to accommodate different plant heights. Key features include:

• Space efficiency: Grow upward instead of outward.
• Modularity: Customizable layouts for crops like leafy greens, herbs, or strawberries.
• Climate control integration: Compatible with LED lighting, irrigation, and ventilation systems.

Vertical farming is ideal for urban environments, warehouses, or regions with limited land.

What Is Hydroponics?

Hydroponics is a soil-free farming method where plants grow in nutrient-rich water solutions. Roots are supported by inert media like perlite, clay pellets, or rockwool. Benefits include:

• Faster growth rates: Direct access to nutrients accelerates plant development.
• Water conservation: Uses up to 90% less water than soil farming.
• Year-round production: Controlled environments eliminate seasonal limitations.

Common hydroponic systems include Nutrient Film Technique (NFT), Deep Water Culture (DWC), and Aeroponics.

Section 2: The Marriage of Vertical Grow Racks and Hydroponics

Technical Compatibility

Vertical grow racks and hydroponics are a natural fit. Here’s why:

1. Modular Design Alignment
   • Hydroponic systems can be scaled vertically using racks. For example, NFT channels or DWC troughs can be installed on each tier.
   • Automated pumps distribute nutrient solutions evenly across tiers.
2. Lighting Optimization
   • LED grow lights can be mounted at each level, ensuring uniform light distribution.
   • Adjustable spectrum LEDs cater to specific crop needs (e.g., blue light for leafy greens, red for fruiting plants).
3. Climate Control Synergy
   • Vertical racks allow precise control of temperature, humidity, and CO2 levels per tier.
   • Closed-loop hydroponic systems minimize water loss through evaporation.

Case Study: Bowery Farming

Bowery Farming, a U.S.-based vertical farming company, uses hydroponic vertical racks to grow over 50 varieties of greens and herbs. Their system integrates:

• Proprietary software to monitor plant health.
• Stacked grow trays with recirculating nutrient solutions.
• Energy-efficient LEDs tailored to each crop’s growth stage.

Result: 100x higher yield per square foot compared to traditional farms.

Section 3: Advantages of Vertical Hydroponic Systems

1. Space Efficiency and Scalability

Vertical hydroponics transforms underutilized spaces (e.g., abandoned warehouses, rooftops) into productive farms. For example:

• Singapore’s Sky Greens: A 9-meter-tall vertical hydroponic farm producing 1 ton of vegetables daily on 0.5 hectares.

2. Resource Conservation

• Water: Closed-loop systems recycle nutrients and water.
• Land: A 10-tier vertical farm can produce the equivalent of 1 acre of farmland.

3. Higher Yields and Faster Harvests

• Lettuce: Grown in 30 days vs. 60 days in soil.
• Strawberries: Year-round production with vertical NFT systems.

4. Reduced Pest and Disease Risk

• Soil-free environments eliminate root rot and soil-borne pathogens.
• Isolated tiers prevent cross-contamination.

Section 4: Challenges and Solutions

1. High Initial Costs

• Setup expenses: Vertical racks, LEDs, and hydroponic infrastructure require significant investment.
  • Solution: Governments (e.g., Japan, Netherlands) subsidize vertical farms to boost food security.

2. Energy Consumption

• LED lighting accounts for ~60% of operational costs.
  • Solution: Solar panels and energy-efficient LEDs (e.g., Philips GreenPower).

3. Technical Expertise

• Maintaining pH, nutrient balance, pipp racks and lighting schedules demands skill.
  • Solution: AI-driven platforms like Plenty Ag automate monitoring and adjustments.

Section 5: Future Trends and Innovations

1. AI and IoT Integration

• Sensors track plant health in real time, adjusting nutrients and light automatically.

2. Hybrid Systems

• Combining hydroponics with aquaponics (fish waste as fertilizer) for closed-loop ecosystems.

3. Urban Farming Expansion

• Companies like Infarm install modular vertical hydroponic units in supermarkets and restaurants.

Conclusion

Vertical grow racks and hydroponics are not just compatible—they’re a powerful duo reshaping agriculture. By merging space-efficient vertical farming with hydroponics’ resource-saving benefits, this technology addresses critical challenges like food security, water scarcity, and urbanization. While hurdles like upfront costs remain, advancements in automation and renewable energy are making vertical hydroponic systems increasingly accessible.

From skyscraper farms in Singapore to modular units in Berlin grocery stores, the future of farming is undeniably upward.