We then present findings from a survey of 35 diverse urban farm operations in the East Bay

Defined in these ways, the radical, transformative potential of urban food production spaces and their preservation often gets lost or pushed to the side in city planning decisions in metropolitan regions such as the San Francisco Bay Area, where the threat of displacement is ubiquitous given high levels of economic inequality and extreme lack of affordable land. In order to facilitate what scholars such as Anderson et al. 2018a refers to as the “agroecological transition,” already underway in many urban food ecosystems around the globe , we argue that applying an agroecological approach to inquiry and research into the diversity of sites, goals, and ways in which food is produced in cities can help enumerate the synergistic effects of urban food producers. This in turn encourages the realization of the transformative potential of urban farming, and an articulation of its value meriting protected space in urban regions. Urban agroecology is an evolving concept that includes the social-ecological and political dimensions as well as the science of ecologically sustainable food production . UAE provides a more holistic framework than urban agriculture to assess how well urban food initiatives produce food and promote environmental literacy, community engagement, and ecosystem services. This paper presents a case study of 35 urban farms in San Francisco’s East Bay in which we investigated key questions related to mission, production , labor, financing, land tenure, and educational programming. Our results reveal a rich and diverse East Bay agroecosystem engaged in varying capacities to fundamentally transform the use of urban space and the regional food system by engaging the public in efforts to stabilize, improve, and sustainably scale urban food production and distribution. Yet, as in other cities across the country,grow trays urban farms face numerous threats to their existence, including land tenure, labor costs, development pressure, and other factors that threaten wider adoption of agroecological principles.

We begin by comparing the concepts of UA and UAE in scholarship and practice, bringing in relevant literature and intellectual histories of each term and clarifying how we apply the term “agroecology” to our analysis. We pay particular attention to the important nonecological factors that the literature has identified as vital to agroecology, but seldomly documents .We discuss the results, showing how an agroecological method of inquiry amplifies important aspects of urban food production spaces and identifies gaps in national urban agriculture policy circles. We conclude by positing unique characteristics of urban agroecology in need of further studies and action to create equitable, resilient and protected urban food systems.Agricultural policy in the United States is primarily concerned with yield, markets, monetary exchange, and rural development. The United States Department of Agriculture defines agricultural activities as those taking place on farms. Farms are defined as “any place from which $1,000 or more of agricultural products were produced and sold, or normally would have been sold, during the year” . Urban agriculture has been proliferating across the country in the last decade on both public and private lands, as both for-profit and nonprofit entities, with diverse goals, missions and practices largely centered on food justice priorities and re-localizing the food system. Yet U.S. agriculture policy has been struggling to keep up. In 2016, the USDA published an Urban Agriculture Toolkit, which aims to provide aspiring farmers with the resources to start an urban farm including an overview of the startup costs, strategies for accessing land and capital, assessing soil quality and water availability, production and marketing, and safety and security . The 2018 U.S. Farm Bill provides a definition of urban agriculture to include the practices of aquaponics, hydroponics, vertical farming, and other indoor or controlled environment agriculture systems primarily geared towards commercial sales. In both the Toolkit and Farm Bill, non-profit, subsistence, and educational urban farming enterprises are not well integrated or included in the conceptualization of UA.

While there are many definitions of urban agriculture in the literature from the simplest definition of “producing food in cities” to longer descriptions of UA such as that of the American Planning Association that incorporate school, rooftop and community gardens “with a purpose extending beyond home consumption and education,” the focus of many UA definitions used in policy arenas continues to center around the production and sale of urban produced foods. Accordingly, food systems scholars have recognized that “Urban agriculture, [as defined], is like agriculture in general”, devoid of the many political, educational, and food justice dimensions that are prioritized by many U.S. urban farming efforts. Thus the social-political nature of farming, food production, and food sovereignty are not invoked by formal UA policy in the U.S. Many goals and activities common in urban food production, including education, nonmonetary forms of exchange, and gardening for subsistence are obscured by the productivist definitions and can be thus neglected in policy discussions. Furthermore, UA policy in the U.S. remains largely agnostic about the sustainability of production practices and their impact on the environment. While U.S. agriculture policy narrowly focuses on the production, distribution and marketing potential of UA, broader discussion of its activities and goals proliferate among food systems scholars from a range of fields including geography, urban planning, sociology, nutrition, and environmental studies. These scholars are quick to point out that UA is much more than production and marketing of food in the city, and includes important justice elements . In the Bay Area context, we continue to see the result of this dichotomy: thriving urban farms lose their leases , struggle to maintain profitability or even viability and encounter difficulties creating monetary value out of their social enterprises. In light of the ongoing challenge to secure longevity of UA in the United States, there is a need for an alternative framework through which food and farming justice advocates can better understand and articulate what UA is, and why it matters in cities.Agroecology is defined as “the application of ecological principles to the study, design and management of agroecosystems that are both productive and natural resource conserving, culturally sensitive, socially just and economically viable” , and presents itself as a viable alternative to productivist forms of agriculture. Agroecology in its most expansive form coalesces the social, ecological, and political elements of growing food in a manner that directly confronts the dominant industrial food system paradigm, and explicitly seeks to “transform food and agriculture systems, addressing the root causes of problems in an integrated way and providing holistic and long-term solutions” . It is simultaneously a set of ecological farming practices and a method of inquiry, and, recently, a framework for urban policy making ; “a practice, a science and a social movement” . Agroecology has strong historical ties to the international peasant rights movement La Via Campesina’s food sovereignty concept, and a rural livelihoods approach to agriculture where knowledge is created through non-hegemonic forms of information exchange, i.e. farmer-tofarmer networks .

Mendez et al. describe the vast diversity of agroecological perspectives in the literature as “agroecologies” and encourage future work that is characterized by a transdisciplinary, participatory and action-oriented approach. In 2015, a global gathering of social movements convened at the International Forum of Agroecology in Selengue, Mali to define a common, grassroots vision for the concept, building on earlier gatherings in 2006 and 2007 to define food sovereignty and agrarian reform. The declaration represents the views of small scale food producers, landless rural workers, indigenous peoples and urban communities alike, affirming that “Agroecology is not a mere set of technologies or production practices” and that “Agroecology is political; it requires us to challenge and transform structures of power in society” . The declaration goes on to outline the bottom-up strategies being employed to build, defend and strengthen agroecology, including policies such as democratized planning processes, knowledge sharing, recognizing the central role of women,dry racks for weed building local economies and alliances, protecting biodiversity and genetic resources, tackling and adapting to climate change, and fighting corporate cooptation of agroecology. Recently, scholars have begun exploring agroecology in the urban context. In 2017, scholars from around the world collaborated on an issue of the Urban Agriculture magazine titled “Urban Agroecology,” conceptualizing the field both in theory and through practical examples of city initiatives, urban policies, citizen activism, and social movements. In this compendium, Van Dyck et al. describe urban agroecology as “a stepping stone to collectively think and act upon food system knowledge production, access to healthy and culturally appropriate food, decent living conditions for food producers and the cultivation of living soils and biodiversity, all at once.” Drawing from examples across Europe, Africa, Latin America and Asia and the United States, the editors observe that urban agroecology “is a practice which – while it could be similar to many ‘urban agricultural’ initiatives born out of the desire to re-build community ties and sustainable food systems, has gone a step further: it has clearly positioned itself in ecological, social and political terms.” . Urban agroecology takes into account urban governance as a transformative process and follows from the re-emergence of food on the urban policy agenda in the past 5-10 years. However, it requires further conceptual development. Some common approaches in rural agroecology do not necessarily align with urban settings, where regenerative soil processes may require attention to industrial contamination. In other cases, the urban context provides “specific knowledge, resources and capacities which may be lacking in rural settings such as shorter direct marketing channels, greater possibility for producer-consumer relations, participatory approaches in labour mobilisation and certification, and initiatives in the area of solidarity economy” .

Focusing on the social and political dimensions of agroecology, Altieri and others have explicitly applied the term “agroecology” to the urban context, calling for the union of urban and rural agrarian food justice and sovereignty struggles . Dehaene et al. speak directly to the revolutionary potential of an agroecological urban food system, building towards an “emancipatory society” with strong community health and justice outcomes. Our research builds upon this emergent body of work that employs urban agroecology as an entry point into broader policy discussions that can enable transitions to more sustainable and equitable city and regional food systems in the U.S. . This transition in UAE policy making is already well underway in many European cities . As noted, there are many dimensions of agroecology and ways in which it is conceptualized and applied. We employ the 10 elements of agroecology recently developed by the UN FAO in our discussion of urban agroecology1 . These 10 elements characterize the key constituents of agroecology including the social, ecological, cultural, and political elements. Despite the emancipatory goals of agroecology, a recent review of the literature by Palomo-Campesino et al. found that few papers mention the non-ecological elements of agroecology and fewer than 1/3 of the papers directly considered more than 3 of the 10 FAO-defined elements. In an effort to help guide the transition to more just and sustainable food and agricultural systems in cities across the U.S., we propose that food system scholars and activists consider using the 10 elements as an analytical tool to both operationalize agroecology, and to systematically assess and communicate not only the ecological, but also the social, cultural and political values of urban agroecology. “By identifying important properties of agroecological systems and approaches, as well as key considerations in developing an enabling environment for agroecology, the 10 Elements [can be] a guide for policymakers, practitioners and stakeholders in planning, managing and evaluating agroecological transitions 2 . We employed a participatory and collaborative mixed methods approach, involving diverse stakeholders from the East Bay Agroecosystem. We held two stakeholder input sessions involving over 40 urban farmers and food advocates to co-create the research questions, advise on the data collection process, interpret the results, and prioritize workshop topics for the community. We administered an online Qualtrics survey to 120 urban farms in the East Bay that had been previously identified by the University of California Cooperative Extension Urban Agriculture working group and additional outreach. The survey launched in Summer 2018, which is a particularly busy time for farmers, and in response to farmer feedback was kept open until November 2018. 35 farmers responded in total, representing a 30% response rate.

The risks of exposing children to residual tobacco smoke contamination are not well understood

Significant differences in concentrations of nicotine in residential dust were observed for all self-reported smoking categories. Pearson correlation coefficients for covariates of interest are shown in Table 15. The group of smoking variables was highly correlated as was the group of parental demographic variables, whereas the two groups of variables were negatively correlated with each other. Other variables correlated with residential-dust nicotine were age of residence, breastfeeding duration, size of sampling area , and vacuum use frequency.Tables 16 and 17 show the results of the principal components analysis for the two groups of highly correlated variables, i.e., self-reported smoking and parental demographics. Three meaningful factors were chosen to represent the 15 self-reported smoking variables and 2 factors were chosen to represent the 5 parental demographic variables. A variable was said to load on a given component if the factor loading was 0.40 or greater . Using this criterion, 12 variables describing parental smoking were found to load on the first smoking component, which was subsequently labeled the parental smoking component. Similarly, the 4 father’s smoking variables loaded on the second smoking component and 3 variables, describing other household smoking, loaded on the third component . Combined, the smoking-related principal components accounted for 65% of the total variance of all smoking variables. The demographic variable group, shown in Table 17 was described by a parental socioeconomic status component, which was loaded by parental education and income, and a parental age component,curing drying which was loaded by the mother’s age and father’s age. Combined, the summary demographic principal components accounted for 80% of the total variance explained by all demographic variables.

Several determinants of concentrations of nicotine in residential dust were identified . Notably, two principal components summarizing self-reported smoking variables were highly significant predictors of residential-dust nicotine in the final models . These principal components represented self-reported smoking for time periods of months and years before dust collection. Based on the regression model results, nicotine concentrations in residential dust seem to reflect cumulative smoking habits of residents over periods of up to several years rather than simply the current smoking pattern in the home. To verify the hypothesis that levels of nicotine in residential-dust samples reflect past smoking habits, it was useful to examine NCCLS households that reported changes in their smoking status between the initial interview and dust collection. Of the households that reported no smoking in the month before dust collection, 90 households had previously reported some smoking at the initial interview. Nicotine concentrations in residential-dust samples from these 90 households did, indeed, remain elevated . This finding suggests that nicotine may contaminant homes long after cigarette smoking has ceased, a phenomenon referred to as “third hand smoke”. In fact, investigators have reported that children living in apartments that were formerly occupied by smokers had elevated levels of residential-dust nicotine and urinary cotinine . Additionally, of the NCCLS households that reported some smoking at the time of dust collection, 5 reported no smoking at the initial interview. These 5 households had lower concentration of nicotine in residential dust than households that consistently reported smoking . Both of these findings support the conjecture that current concentrations of nicotine in residential dust may be particularly good measures of cumulative household smoking habits. Furthermore, these findings suggests that, in studies that aim to estimate prenatal or postnatal cigarette smoking exposures retrospectively, concentration of nicotine in residential dust could be a more useful surrogate than short-term exposure markers such as concentrations of nicotine in air or of cotinine in urine. After considering self-reported smoking, the age of the residence was a significant predictor of concentrations of nicotine in residential dust. Since concentrations of nicotine in residential dust increase with the age of the residence,nicotine evidently accumulates in household carpets. Thus, nicotine concentrations in residential dust likely reflect cumulative smoking habits in a household. Two measures of parental demographics, namely, the parental SES component and the parental age component, remained significant predictors of the concentrations of nicotine in residential dust, after accounting for self-reported smoking.

Table 19 illustrates that, in general, after adjusting for self-reported smoking, concentrations of nicotine in residential dust decreased with increasing parental SES and age. Interestingly, when considering the 211 households that reported no smoking at any time, the households with below median income had significantly higher concentration of nicotine in their residential dust than the households with above median income . Thus, even when no smoking was reported, low-income households had elevated concentrations of nicotine in their residential dust compared to high-income households. There are several possible explanations for the discrepancy in levels of nicotine in residential dust from self-reported non-smoking households: low-SES residences may be physically different from high-SES residences, due to unmeasured differences in ventilation, carpet types, light, moisture or microbial action; low-SES parents may be more likely to be exposed to passive cigarette smoke, and may convey nicotine into their homes on their skin or clothing; low-SES households may be more likely to have residual nicotine in residential dust from previous residents; low-SES households may use more smokeless tobacco products or; low-SES households may have under reported their smoking habits. If differential self-reporting by SES or age is present, then an objective measure of exposure to household smoking, such as concentrations of nicotine in residential dust, would be advantageous. Three other variables were significant predictors of nicotine concentrations in residential dust after adjusting for self-reported smoking and parental demographics, residence is apartment, residence is townhouse, and size of sampling area. Since apartments and townhouses generally have less square footage than single family homes, the positive regression coefficient for the variables residence is apartment and residence is townhouse are consistent with the observation of Hein et al. who found that residential-dust nicotine concentrations increased with decreasing square footage of the residence. The negative regression coefficient for the variable size of sampling area in the final model with HVS3-sampled homes indicates that, as the size of carpet sampled increased, the concentration of nicotine measured in residential dust decreased.

This relationship could be a limitation of the HVS3 sampling method and it suggests that this variable should be measured and adjusted for in models of residential-dust nicotine concentrations using HVS3 sampling. Still,drying curing including size of sampling area in the regression model had little effect on the other parameters. Given that the ultimate purpose of the NCCLS is to compare leukemia cases and controls, the effect of case-control status on measured nicotine concentration was examined. Interestingly, case-control status was not a significant predictor of nicotine concentrations and there was no indication that case parents were reporting their smoking differently than controls . This finding suggests that there was little differential misclassification of exposures in case and control households in the previous analysis of self-reported cigarette smoking in the NCCLS population . The concentrations of nicotine measured in dust from smoking and non-smoking NCCLS residences were lower than those previously reported . Specifically, the median concentrations of nicotine for self-reported non-smoking NCCLS homes was 0.3 µg/g, substantially lower than median levels reported for non-smoking homes in previous studies . As discussed in Chapter 1, lower levels of background nicotine contamination might be explained by the low prevalence of smoking in California. Alternatively, these differences may partly reflect differences in analytical methodology. Despite the lower levels of nicotine measured in the NCCLS, the nicotine concentrations in residential-dust samples were correlated with concurrently self-reported household cigarette consumption . Although concentrations of nicotine in residential dust are specific indicators of cigarette smoke contamination, the use of dust to assess children’s exposure to secondhand cigarette smoke has limitations. First, it must be assumed that children are in the home when smoking occurs. This is a reasonable expectation given the young age of the children in the NCCLS . Secondly, it must be assumed that nicotine in residential dust originated from cigarettes smoked in the home. However, a previous study found that nicotine levels in residential dust were elevated in homes where parents reported only smoking outdoors compared to homes where parents reported no smoking . Thus, parents that are exposed to cigarette smoke may convey nicotine into carpets, via their skin, clothing, or shoes without exposing their children to secondhand cigarette smoke.Future studies should consider using a long-term biomarker of exposure to cigarette smoke, such as hair nicotine, to investigate the relationship between concentrations of nicotine in residential dust and the corresponding biological dose of nicotine in children. Since parents may have tracked nicotine into their homes after smoking outside, the results of the residential-dust nicotine models may have been somewhat obscured. Specifically, the variable describing household cigarette consumption during the month before dust collection was specific to in-home smoking and it was a relatively weak predictor of nicotine concentrations in dust.

In contrast, the highly significant parental and father smoking components were based on general smoking habits . It is possible that the variable describing household cigarette consumption during the month before dust collection was a relatively weak predictor of nicotine levels, because outdoor smoking was excluded. In summary, results reported in this chapter confirmed previous findings that concentrations of nicotine in residential dust were significantly associated with self reported household smoking. Chapter 3 also presents evidence that residual smoke contamination , could persist in homes long after cigarette smoking ceased. Finally, these results suggest that concentrations of nicotine in residential dust can be used as long-term surrogates for exposures to cigarette smoke in the home. Polycyclic aromatic hydrocarbons are formed as products of incomplete combustion and there are a variety of indoor PAH sources including cigarette smoke, wood-burning fireplaces, gas appliances, and charred foods, as well as outdoor sources, including vehicle exhaust and coal-tar-based pavement sealants . Occupational exposures to PAHs have been associated with increased risks of lung, skin, and bladder cancers . Likewise, increased levels of PAH-DNA adducts have been associated with lung cancer in the general population. Moreover, in-utero PAH exposures, as measured by maternal personal air monitoring during pregnancy, have been associated with IQ deficits , cognitive developmental delays , decreased gestational size , and respiratory effects . Surrogates of PAH exposure have been measured in several environmental and biological media, including air , residential dust , urine , and blood . Because chemicals can accumulate in carpets , concentrations of PAH in residential dust may be long-term predictors of indoor PAH exposures. Moreover, because inadvertent dust ingestion could be responsible for as much as 42% of non-dietary PAH exposure in young children , levels of PAHs in residential dust may be particularly relevant to the uptake of PAHs in children. Although measurements of chemicals in residential dust are specific measures of indoor exposures, such data have rarely been collected in epidemiologic investigations. Rather, epidemiologists have classified potential exposures to chemicals based on selfreported information and/or ambient levels of chemicals measured at outdoor monitoring sites. Since self-reports and estimated outdoor air levels may not be good surrogates for indoor exposures, it is important to know the extent to which these indirect measures predict residential levels of environmental agents. Chapter 4 evaluates the predictive value of self-reported and geographic data in estimating measured levels of 9 PAHs in residential-dust samples. A global-positioning-system device was used to determine the latitude and longitude coordinates for each residence. Subsequently, three surrogates for outdoor PAH concentrations: traffic density, modeled predictions of outdoor PAH concentrations, and urban or rural location were considered. Traffic density was estimated as described previously . Briefly, a 500-m radius was drawn around each residence and traffic density was defined as the sum of the annual average daily traffic count from 2000, multiplied by the length of the road for all roads within the buffer, divided by the buffer’s area . The estimates of outdoor PAH concentrations were taken from the EPA’s 2002 National-Scale Air Toxics Assessment . The outdoor PAH concentrations were estimated at a census-tract resolution using an air dispersion model and National Emissions Inventory data, which includes major stationary sources , area sources , and mobile sources .

Growers who completed the survey were also clearly knowledgeable about cannabis cultivation

Growers were likely referring to hemp russet mite , two-spotted spider mite , broad mite and Carmine spider mite , respectively, but this remains unclear because there are many species of mite commonly referred to as russet mite, spider mite and red mite . This similarly applies to aphids, thrips, larvae, mildew, rots and molds. Accurate species identification of these pests and diseases will remain uncertain until they can be more systematically collected and identified by UC academics or other scientists. The most common approach to pest and disease control was to apply some type of solution or chemical to the crop , followed by augmentation of natural enemies and various cultural practices .A majority of sprays were products that were biologically derived or approved for use in organic production. Products specifically used for control of arthropod pests included azadirachtin , soap solution , pyrethrins and Bacillus thuringiensis . Many respondents indicated that certain products were effective against both pests and diseases, for instance microbial pesticides , oils and compost tea . Sulfur was the most commonly applied product specifically used for disease control. In addition, 29% of respondents claimed to use certified organic products for pest and disease management but did not name any product specifically. Finally, 2% of respondents reported that they did not spray for pests and diseases at all. Augmentation of natural enemies involved the introduction of predatory mites , lady beetles , predatory nematodes and other unnamed beneficial insects . Cultural practices included removal of infested plant material , insect trapping , intercropping , use of diatomaceous earth and selection of resistant cultivars .Our survey, although of limited sample size,weed curing is the first known survey of California cannabis growers and provided insights into common forms of cultivation, pest and disease management, water use and labor practices.

Since completing this survey, we have discussed and/or presented the survey results with representatives from multiple cannabis grower organizations, and they confirmed that the data were generally in line with production trends. Evident in the survey results, however, was the need for more data on grower cultivation practices before best management practices or natural resource stewardship goals can be developed. All growers monitored crop health, and many reported using a preventative management strategy, but we have no information on treatment thresholds used or the efficacy of particular sprays on cannabis crops. Likewise, the details of species-level pest and disease identification, natural enemy augmentation and sanitation efforts remain unclear. Growers did not report using synthetic pesticides, which contrasts with findings from previous studies that documented a wide range of synthetic pesticide residues on cannabis . Product selection for cannabis is very limited due to a mixed regulatory environment that currently does not allow for the registration of any insecticide or fungicide for use specifically on cannabis , although growers are allowed to use products that are exempt from residue tolerance requirements, exempt from registration requirements or registered for a use that is broad enough to include cannabis . As such, it may be that in the absence of legally available chemical controls growers were choosing allowable, biologically derived products or alternative strategies such as natural enemy augmentation and sanitation. Our survey population was perhaps biased toward non-chemical pest management — the organizations we contacted for participant recruitment included some that were formed to share and promote sustainability practices. Or, it may be that respondents were reluctant to report using synthetic chemicals or products not licensed for cannabis plants. The only other published data on water application rates for cannabis cultivation in California we are aware of is from Bauer et al. , who used estimates for Humboldt County of 6 gallons per day per plant for outdoor cultivation over the growing season .

Grower reported estimates of cannabis water use in this survey were similar to this rate in the peak growing season , but was otherwise lower. Due to the small sample size, we cannot say that groundwater is the primary water source for most cannabis growers in California or that few use surface water diversions. However, Dillis et al. found similar results on groundwater being a major water source for cannabis growers, at least in northwest California. If the irrigation practices reported in our survey represent patterns in California cannabis cultivation, best management practices would be helpful in limiting impacts to freshwater organisms and ecosystems. For example, where groundwater pumping has timely and proximate impacts to surface waters, limiting dry season groundwater extraction by storing groundwater or surface water in the wet season may be beneficial , though this will likely require increases in storage capacity. The recently adopted Cannabis Cultivation Policy requires a mandatory dry season forbearance period for surface water diversions, though not for groundwater pumping. Our survey results indicate that the practical constraints on adding storage may be a significant barrier for compliance with mandatory forbearance periods for many growers. More in-depth research with growers and workers is needed to explore the characteristics of the cannabis labor force and the trajectory of the cannabis labor market, especially in light of legalization. Several growers commented on experiencing labor shortages, a notable finding given that recent market analyses of the cannabis industry suggest that labor compliance costs are the most significant of all of the direct regulatory costs for growers. Higher rates of licensing compliance among medium and large farms is not surprising given the likelihood that they are better able to pay permitting costs. Yet, that the majority of respondents indicated they had not applied for a license to grow cannabis, with over half noting some income from cannabis sales, indicates potentially significant effects if these growers remain excluded from the legalization process. More research is needed to understand the socioeconomic impacts of legalization, which likely extend beyond those accounted for in the state’s economic impact analysis, which primarily focuses on economic contributions that a legalized market will bring to the state .

Bodwitch et al. report that surveyed growers characterized legalization as a process that has excluded small farmers, altered local economies and given rise to illicit markets. The environmental impacts of drying cannabis production have received attention because of expansion into remote areas near sensitive natural habitats. The negative impacts are likely not because cannabis production is inherently detrimental to the environment, but rather due to siting decisions and cultivation practices. In the absence of regulation and best management practices based on research, it is no surprise that there have been instances of negative impacts on the environment. At the same time, many growers appear to have adopted an environmentally proactive approach to production and created networks to share and promote best management practices. Organizations that we approached to recruit survey participants had a fairly large base membership , which is on a par with other major commodity groups, like the Almond Board of California and California Association of Wine grape Growers . Membership included cannabis growers, distributors and processors as well as interested members of the public, and some people were members of more than one organization, suggesting a large, engaged community. Most of the organizations we contacted enthusiastically agreed to help us recruit growers for our survey, and we received excellent feedback on our initial survey questions. Some potential future research topics include the development of pest and disease monitoring programs; quantifying economic treatment thresholds; evaluating the efficacy of different biological, cultural and chemical controls; developing strategies to improve water use and irrigation efficiency; understanding grower motivations for regulatory compliance; understanding the impacts of regulation; and characterizing the competition between labor in cannabis and other agricultural crops — to name just a few. As cannabis research and extension programs are developed, it will be critical to ensure that future surveys capture a representative sample of cannabis growers operating inside and outside the legal market, to identify additional areas for research and develop best practices for the various cultivation settings in which California cannabis is grown. In the United States, Native Americans experience a dramatically higher burden of diet-related chronic disease across the lifespan compared to the all-race population. Approximately 38% of NA adults are obese, and research from 2016 reports that preschool-aged NA and Alaska Native children had the highest obesity rates compared to all racial groups combined. During childhood, establishing healthy eating habits is vital for physical growth and cognitive development. Moreover, research has shown that a diet rich in vegetables during childhood can help protect against chronic diseases, such as obesity, heart disease, and diabetes, that develop during adulthood. Though data on diet quality of NA populations are limited, prior studies that included NAs found that diet quality is insufficient and is lower than in other populations. Preschool-aged children consume almost half of their daily calories at school, which is an important setting for food environment interventions. Childcare-based interventions are effective in improving nutrition behaviors among children and are recognized as a vital influence on learned eating behaviors. However, most of these nutrition programs have been implemented in urban schools, and little is known about school-based interventions among rural NA communities. Tribally owned and operated Early Childhood and Education programs offer preschool-aged children around two snacks and two meals per day and signify a vital organizational influence on childhood obesity disparities. Therefore, ECEs can serve as an essential location to provide healthy eating interventions for NA children.

School gardens are a common strategy to increase fruit and vegetable intake in all grades, including ECE programs; however, limited studies have used rigorous methodological designs to assess their impact on diet quality and health outcomes. A systematic review on garden-based interventions among preschoolers found that only four studies assessed fruit and vegetable intake, and only one has been conducted among NA youth. Results from this study found that increases in preferences for vegetables were significant, but intake was not . To our knowledge, there are no studies that address vegetable intake and health outcomes among NA children in ECE programs using a multi-level method, targeting the individual, family, and community. Using a community-based participatory research approach, we partnered with the Osage Nation to implement the Food Resource Equity and Sustainability for Health study, a culturally based farm-to-school intervention to increase vegetable intake among NA children and their families. The intervention was implemented within Osage Nation ECEs. The aim of this manuscript is to describe the FRESH intervention results, including changes in dietary intake , body mass index , systolic blood pressure , health status, and food insecurity among Osage Nation families. The six-month FRESH study employed a randomized wait-list controlled trial design with treatment condition assigned at the community level . The design and methods of the FRESH study have been published in detail elsewhere. In summary, our tribal-university partnership recruited NA families of children attending Osage Nation ECE programs in four communities to assess individual-level changes on children and adults. Two communities received the intervention and two communities served as wait-list controls. We randomized by community instead of ECE program to avoid crossover due to geographical proximity to members of the other study group. The FRESH Leadership Committee included four university researchers and 13 Osage Nation employees from the health, education, language, agriculture, and government divisions and led all aspects of the study. University researchers set up tables in ECE programs during school orientation, back-to-school nights, and during child drop-off/pickup to notify parents about the study and invite them to participate.ECE staff also contacted parents to notify them about the study. FRESH study flyers that promoted the study were shared through children’s backpacks and parent mailings. Flyers were also posted in classrooms around the schools. Adults at least 18 years old who met the following inclusion criteria were eligible to participate in the study: one or more family member in the household identified as NA; one or more child between the ages of three and six years enrolled at an Osage Nation ECE program; planned to reside in Osage Nation for nine months or more; and one or more adult family member willing to engage in monthly family nights at the school. Children were eligible if they were between the ages of three and six years old, enrolled in a participating ECE program, and were a household family member of an eligible adult.

Pastoral communities are those whose means of living entirely depends on raising livestock

There are two contrary debates focused on whether pastoral lifestyles could serve as an adaptation strategy to climate change in the drylands regions of East Africa. The first contends with deep pessimism about the pastoral mode of life, viewing pastoralism an old living system by which pastoralists could not meet their livelihood requirements. Pastoralists live in drylands areas characterized by repeating droughts, land degradation, lack of marketing, governance and access to technology . And even these limited resource regions are being further stressed by human population growth. In the Greater Horn of Africa, pressure on the ecological base of rangelands threatened carrying capacity to support huge livestock herds that eventually left pastoralists in crisis . According to Sandford , introducing improved livestock management with permanent settlement should be prioritized and this can be credible if it is integrated with irrigation and mixed livestock-cereal production and with forage enhancement schemes. His argument emphasizes that settling pastoral communities into permanent locations leads to the provision of basic infrastructure including schools, health services, road accesses, and veterinary services. The second strand of literature strongly advocates the importance of the pastoral living style to maintain livelihoods through traditional systems . Pastoralists have a long history of involvement in various forms of adaptation methods based on their own indigenous knowledge . Research findings demonstrate that the pastoral system is an easy way to adapt to climatic effects, owing to its suitability to arid and semi-arid environments through strategies of establishing strong social capital, economic cooperation among community members and clan lineage networks, herd diversification and restocking methods. In such a context, pastoral life allows the community to keep their cultural systems and knowledge while responding to the negative effects of climate change. Instead of changing the prolonged indigenous mode of living into the proposed new style of life,horticulture trays more attention is needed to enhance mobility strategies in a way that supports adaptive capacity by introducing modern extension services and veterinary facilities. Clearly, there is a divergence of opinions about the sustainability of the pastoral way of life and its corresponding contribution towards climatic adaptation in the drylands regions of Africa.

This is complicated by the multifaceted nature of adaptation possibilities that are heavily dependent on a variety of factors such as market accessibility and institutions , resource availability , demand pressure of human and livestock populations for limited land size and availability of livelihood options apart from livestock earnings . Considering the existence of pastoral, semi-pastoral, agro-pastoral and mixed-farming communities in the region, it is difficult to clearly point out exactly how these two debates fit into policy actions without having sizeable evidence. This requires a thorough investigation about how multiple adaptation strategies influence the adaptive capacity of these communities. This study examines what and how major factors influence the adaptive capacity of rural communities in the Afar region of Ethiopia, including to what extent adaptation methods are applied and which adaptation methods contribute to household income. This is important because rural communities in the Afar region account for about 29% of the country’s total population and 16% per annum of total GDP 2008). While most of these communities meet their subsistence living via engaging in animal production, the natural resource base in the region is highly subject to overgrazing and deforestation, with an increasing number of human and livestock populations , which has accelerated . Such challenges combined with unpredictable rainfall and changing temperature leave villagers vulnerable to economic disasters. Therefore, understanding how locally practised adaptation strategies uphold the livelihoods of rural communities is paramount to improve their lives. It is unclear which adaptation strategies lift livelihoods across the community groups. The large body of previous literature is focused on climate modelling techniques for identifying future threats of climate change and outlining adaptation approaches. Options for adaptation include diversifying income, building formal and informal institutions, adjustments in livestock holdings and species, labour mobility and engagement in small irrigation schemes . However, little empirical knowledge is available to help understand the effects of alternative adaptation strategies on household incomes. Hence, this study has three objectives: to determine how pastoral, semi-pastoral, agro-pastoral and mixed-farming communities perceive the effects of climatic change; to examine how they adapt to these changes and to estimate how that affects their income. Results are based on a survey of over 300 pastoral, semi-pastoral, agro-pastoral and mixed-farming communities.The Aba’ala district was chosen for two reasons. First, the district is characterized by its dryness and the common phenomenon of drought occurrences for about five decades.

Due to its geographical remoteness from the Awash River and other perennial rivers, Aba’ala is one of the districts in northern Afar currently suffering from lack of water and access to grazing areas during drought periods. Second, the existence of indigenous experiences of adaptation methods practised by pastoral, semipastoral, agro-pastoral and mixed-farming communities in the district motivated this research, specifically to formulate a detailed analysis on relationships between various adaptation strategies and household income. The livelihood bases of the Afar communities depend on their involvement in livestock rearing, cropping and mixed crop-livestock farming systems. Household adaptation strategies vary across communities in Aba’ala district .These communities are widely known for managing their livestock through a nomadic strategy. They pursue livestock mobility in search of natural pasture and water sources. Semi-pastoral community members are those who were originally pure pastoralists but started to evolve into cropping over the last three decades. Although these communities are land owners, their involvement in cropping is only through renting or sharecropping to other farmers. Their livelihood dominantly depends on livestock rearing with a sedentary lifestyle in permanent houses. Their adaptation strategies to climate change and drought include livestock mobility, sharecropping, trading and participating in some other off-farm activities such as wages and salaries. The agro-pastoral community members mainly raise cattle, have their own land and directly produce cereals. They cope with adverse events of climate change by collecting animal feed . The mixed crop-livestock farming community members have their own land and rent-in or share-in cultivable land from others . The main source for their living is crop farming. They keep raising a small number of cattle for draught power and small ruminant animals to supplement their produce from cropping. Data from the four communities were collected in two stages of primary surveys. First, a reconnaissance appraisal was conducted to have a broader understanding on adaptive behaviours of farmers that dwell in the study area. During the exploratory survey, a series of discussions were held with various stakeholders including clan leaders, farmers, pastoralists, agro-pastoralists, extension workers and agricultural experts.

Pertinent information obtained from the first stage was used to refine the study objectives,sliding grow tables sampling methods and the survey instrument. In the second stage, we stratified the community into mixed-farming, agro-pastoral, semi-pastoral and pastoral, whereby sample households were selected from each stratum randomly. Based on the four community classifications, sampling across 11 Kebeles in the Aba’ala districts was made. Out of the 11 Kebeles, five were pastorals, three were semi-pastorals, one was agro-pastoral; the remaining two are mixed-farming communities. To ensure appropriate representation of each stratum, a two-stage stratification sampling method was applied to minimize heterogeneities among groups . In total, there were about 2,236 households across the four groups. Proportionately, the number of households in each stratum constituted 763 pastoral, 287 semi-pastoral, 508 agro-pastoral and 678 mixed-farming communities. In the end, 325 representative sample households were randomly selected from the four groups, out of which, 110 were pastoral, 43 semi-pastoral, 74 agro-pastoral and 98 mixed-farming communities. Among those 325 household heads randomly selected for sampling, we were unable to collect data from 12 households due to change in their address during the five consecutive years. Hence, a balanced panel data of 313 sample households was gathered in 2011, 2012, 2013, 2014 and 2015. To preclude seasonal variations, data collection was conducted every November. Four enumerators who have good knowledge regarding the study area were hired and trained for the survey. After developing and completing preparation of the structured questionnaire, a pre-test survey was conducted on 12 households, the feed backs of which were incorporated in the full survey. Qualitative data were also gathered to supplement data types that cannot be obtained via quantitative methods.This would validate the quantitative results to come up with story lines of information about local practices of adaptation to climate change for improving their livelihood sources. Before setting out on fieldwork for data collection, clan leaders, religious leaders, agricultural experts, village administrators and elders were selected to hold group discussions. The important criterion for the inclusion of such discussions in this context was based on their pertinence for substantiating the findings. During the discussion, ethnographical methods were used to explore the contribution of Afar communities and highland settlers in building livelihood assets.As shown in Table 1, the mean age of households was 48.9 years. A given household constituted an average family size of six members whose age ranged between 15 and 64 years.

According to International Labor Office , this age category is termed as the active economic labour force population. This shows that the availability of the active labour force in rural areas is an opportunity to apply locally based adaptation strategies. For instance, a physically capable labour force can easily accomplish various environmental conservation actions, which would enable the locals to cope with risks related to climatic change. The implication is that local development plans that incorporate participation of an active labour force across rural villages may enhance sustainable income options and minimizing climate-related risks. The study findings also indicated that the average size of families whose age was below 15 and greater than 64 years were 3 and 0.09, respectively. The ILO named these age categories as a dependent labour force. In terms of gender distribution, 84% of the household heads were males and the remaining 16% were females. Based on ideas obtained from key informants and group discussants, females in the Afar region were generally burdened with indoor family management tasks, which deterred them from accessing various income-generating activities such as possible benefits from livestock rearing and off-farm activities. The result is consistent with other studies conducted by Chala et al. and FAO . Females in Ethiopia have cultural hindrances that obstruct their involvement in various developmental activities outside their home. Women are highly engaged in family management and indoor house duties such as cooking, washing and taking care of their children. Because of these extra burdens, it is hard for them to access formal education and work outside homes seeking to supplement their financial situations. Among the household heads, 66.9% did not get any chance to get a formal education, 19.6% could write and read, 13.5% reached primary level, and nobody went to secondary school. It was presumed that more educated people would have more awareness about the effects of climate change and ability to apply adaptation measures. The mean level of household’s working experience in livestock farming was almost 25 years. The major livestock holdings across the household heads were cattle , goats, sheep and camels . Among livestock owners who already moved to other potential areas, 6% reported that they continued moving for more than one month until they get sufficient pasture and water sources. Once livestock owners moved to a certain district, they no longer keep moving if they find sufficient feed for their cattle. In the study, a majority of livestock owners did not make repeating movements after they found adequate feed resources in certain areas. Hence, accessibility to animal feed and water resources determines household’s movement.Households were requested to provide their views about whether they were sensitive to the effects of climate change. The majority reported that successive occurrences of droughts and the vulnerable nature of livestock farming in the Afar region had heightened their sensitivity in terms of crop failure and animal decimation over the last five years. Table 2 presents information about the perception of household heads across the four community groups and the degree of climatic effects they perceived.

Environmental harms resulting from accelerated erosion are well documented

Therefore, removing sick or dead birds from the pens likely did not prevent secondary exposure from contaminated litter or soil, which is the primary mode of transmission for MSD virus . The farm in Stanislaus County was the only game bird producer near commercial poultry producers. This farm was also the largest with approximately 40,000 pheasants and 60,000 chukar raised annually. Likely due to the size of this farm, they employed a greater level of bio-security relative to the other farms that participated in the survey. The Stanislaus farm had bio-security signage at the entrance to the property, as well as foot baths at the entrances to every brooder house. They employed a variety of wildlife control measures, including traps and rodent bait stations, to minimize the interaction of wildlife with pheasants or other game birds raised on the property. Although farms did not have a vehicle wash station, they did not allow people to come on the property without prior authorization. Only two of five farms used a wash station of any kind that was separate from foot baths, and two farms required vehicles to remain outside of the farm perimeter when clients or vendors visited the property . Although game breeders interviewed during the study did not always adhere to bio-security guidelines recommended by NPIP, in general, they understood the importance of minimizing points of contact that could lead to pathogen transmission on the farm. They did not share equipment such as crates, trailers or other farming equipment with other breeders. They also stated that they used their own vehicles and personnel to transport birds to release sites or to clients purchasing birds across state lines. Game breeders sought to balance bio-security on the farm with the size of their flocks,dutch bucket hydroponic and implementation of bio-security guidelines was not necessarily equivalent to the game breeders’ understanding of bio-security.

Rather, farmers likely weighed the risk of not following certain bio-security principles with the cost of implementing that principle. However, adequate surveillance and preventive action is still likely the best means of minimizing the potential for disease to be released into wildlife environments or otherwise spill over into backyard flocks or commercial poultry.In the last 40 years, 30 percent of the world’s arable land has become unproductive and 10 million hectares are lost each year due to erosion.1 Additionally, accelerated erosion diminishes soil quality, thereby reducing the productivity of natural, agricultural and forest ecosystems. Given that it takes about 500 years to form an inch of topsoil, this alarming rate of erosion in modern times is cause for concern for the future of agriculture. This supplement explores the major causes of soil erosion and the social impacts it has on communities, underscoring the importance of agricultural practices that prevent or minimize erosion. Anthropogenic causes of accelerated soil erosion are numerous and vary globally. Industrial agriculture, along with overgrazing, has been the most significant contributor, with deforestation and urban development not far behind.2, 3, 4 Heavy tillage, fallow rotations, monocultures, and marginal-land production are all hallmarks of conventional agriculture as it is variably practiced around the world and significantly encourage accelerated soil erosion. Repeated tillage with heavy machinery destroys soil structure, pulverizing soil particles into dust that is easily swept up by wind or water runoff. Fallow rotations, common with cash crops around the world and subsidized in bio-fuel production in the U.S., leave land vulnerable to the full force of wind gusts and raindrops. Monocultures tend to be planted in rows, exposing the soil between to erosion, and are commonly associated with fallow rotations. More and more marginal land, land that is steep and particularly susceptible to water erosion, is being planted by farmers either attracted by higher crop prices or forced by loss of productivity on flatter, but already eroded lands. In an increasingly complex global food web, seemingly separate causes of erosion begin to influence each other, magnifying their effects. For example, deforestation of tropical forests in Brazil clears the way for industrial soybean production and animal grazing to feed sprawling urban populations in the U.S.

All the while, fertile topsoil is carried away by wind and water at alarming rates. Decreased soil fertility and quality, chemical-laden runoff and groundwater pollution, and increased flooding are just a few of these detrimental effects. There are, in addition, disproportionate social harms resulting from high rates of erosion that are less obvious, but no less directly linked. Hunger, debt, and disease are serious problems in mostly poor, rural communities around the world that are exacerbated by accelerated erosion. As global agricultural development and trade have accelerated in the last half-century, mainly via the “green revolution” and the formation of the World Trade Organization , increasing trade pressures have raised export crop production in less developed countries. As a result, farmers mainly in Asia, Latin America, and sub-Saharan Africa are increasingly abandoning traditional farming techniques and locally significant crops in favor of adopting the industrial practices mentioned above that lead to high rates of erosion.5 While development institutions and governments proclaim concerns for the rural environment, agricultural policy supporting high commodity prices and limited credit access continually pushes farmers to intensify land use. Coupled with the fact that the total area of arable land in cultivation in these parts of the world is already very high , land degradation by soil erosion threatens food security by removing from cultivation land sorely needed for domestic food production. The majority of the world’s 868 million undernourished people live in Eastern and Southern Asia and sub-Saharan Africa. One of the international responses to soil degradation in the developing world has been to promote soil conserving tillage practices known as minimumor no-till agriculture. No-till agriculture protects soil by leaving crop residue on the field to decompose instead of plowing it into the ground before planting the next crop. Weed management is addressed with heavy herbicide use to make up for the loss of weed control from tillage. The practice, extensively adopted in the U.S., has been popular in Brazil and Argentina, and much effort is being expended to expand no-till to Asia and Africa. There are, however, costs associated with no-till agriculture, both economic and social. First, no-till agriculture is expensive to adopt. Herbicides, seed drills, fertilizers, and other equipment require a high initial investment not possible for poor farmers without incurring significant debt. Second, heavier herbicide use increases human exposure to chemicals and contributes to water and air pollution. Third, weed pressures can change in unexpected ways as reliance on a handful of herbicides breeds resistance. Weed resistance to the popular herbicide, glyphosate, is an increasing concern in conventional agriculture and is leading to development of more harmful herbicides to compensate for glyphosate’s reduced effectiveness.

Lastly, no-till agriculture alsopromotes monoculture cropping systems that, as described above, have a deleterious effect on soil quality. The techniques illustrated in this manual emphasize long-term soil stewardship using an integrated approach to soil health and management. For example,dutch buckets system cover crops hold soil aggregates together in the wet season, protecting soil from the erosive effects of rain. Properly timed tillage limits its destructive effects on soil particles and soil structure. Compost promotes a healthy soil ecosystem, improving soil’s structure and its ability to more successfully withstand wind and water erosion. In addition to environmental benefits, agroecological systems are often based on traditional farming practices that promote soil-conserving techniques and varietal choices adapted to the particular region, stemming the tide of land consolidation and commodity crop production. Food security is enhanced and debt risk reduced by way of diverse cropping systems and labor-intensive, rather than input intensive, production methods. And there are public health benefits from eliminating exposure to harmful pesticides and herbicides. In sum, the serious challenge presented by accelerated soil erosion coupled with the uncertainty about whether no-till agriculture’s benefits outweigh its harms underscores the importance of employing an agroecological approach to farming that prevents soil erosion on farms.The Parisian market gardens for which the practice was originally named were small plots of land that were deeply and attentively cultivated by French gardeners, or “maraîchers.” The “marais” system, as it is known in French, was formed in part as a response to the increasing urbanization of Paris, the attendant increase in the cost of urban land, and the ready availability of horse manure as a fertility source. English master gardener Alan Chadwick popularized both the term and the gardening method in the U.S. when he introduced them at UC Santa Cruz’s Student Garden Project in 1967, and they have served as the theoretical foundation supporting the cultivation methods used at the UCSC Farm & Garden ever since. But as Chadwick was quick to point out, other societies were using similar practices far earlier than the Parisian market gardeners. He acknowledged the influence of early Chinese, Greek, and Roman agriculture specifically, on the development of the French-intensive method.

The concept of small farms dedicated to intensive cultivation of the land, improved soil fertility, water conservation, and closed-loop systems was a feature common to many early civilizations and, in fact, characterizes the majority of agriculture today in developing countries where these techniques have been passed down to successive generations. Of the world’s 525 million farms, approximately 85% are fewer than 4 acres in size, tended to mostly by poor farmers in China, India, and Africa,1 where methods often reflect the same philosophies of stewardship and cultivation that inform the French intensive method we use today. In fact, small-scale agriculture represents the global history of agriculture up until the Industrial Revolution in the 18th century. And in much of the developing world, locally adapted traditions continue to shape the way agriculture is practiced. This supplement examines some of the methods used by farmers around the world, past and present, reflecting the principles on which the French-intensive method is based.As part of one of the oldest agriculture-based societies in the world, Chinese farmers have succeeded in maintaining fertile soils for thousands of years. Prior to the availability and use of synthetic fertilizers, one method Chinese farmers commonly used to maintain their soil’s fertility was to apply human waste to their fields, thereby returning large quantities of potassium, phosphorous, and nitrogen lost through harvest back to the soil. Applying this source of fertilizer, also called “night soil,” achieved many of the goals we aspire to in a French-intensive system. Recycling waste minimized external inputs and helped “close the system” by relying on a renewable, readily available source of fertilizer. High in organic matter, night soil also provided the necessary nutrients for growing successive crops on the same land without depleting the soil. Waste, both human and animal, served as the major source of fertility amendments that helped to build soil ecology and microbial activity.In Japan, compost production has been tied to small-scale farming for centuries. Farmers harvested herbaceous growth from nearby hillsides as a source of compost material. Compost houses were built and filled with this herbage, manure, and soil daily until piles reached five feet high. Water was constantly added to ensure saturation. Once the designated height was reached farmers let the piles sit five weeks in summer and seven weeks in winter before turning them to the other side of the house. The compost was then applied to dry land cereal crops in spring. A study conducted in the early 20th century found that nitrogen, phosphorus, and potassium were replenished by this composting system nearly at the level lost through harvest.2This study evaluated the efficiency of CDC-LT used with or without CO2 baits and placed inside or outside of residential dwellings in northwestern Thailand. This is the first in-depth survey and analysis, seeking to provide some guidelines for CDC-LT-based mosquito trapping studies and surveillance programs in this region of Thailand. Overall, CO2 baits significantly increased trapping efficiency of Anopheles spp. mosquitoes , especially when the traps were placed outside of residential dwellings. Stratification by season revealed that the effect was restricted to observations in the hot-season . Generally, the most abundant Anopheles species, An. minimus s.l. was captured preferentially in indoor traps, which is likely related to its anthropophilic nature.

Firms producing animal products and grapes anticipate the least use

Nation of birth, prohibited as a basis for screening and as a topic of pre-employment inquiry, is nevertheless considered in 12 percent of farm businesses, least of all by the largest employers. What else do farmers look for in prospective production employees? Respondents overwhelmingly confirm the importance of criteria listed in the questionnaire, 95 percent or more citing as major 0rIninor factors: reliability in coming to and staying at work on schedule, skills of the kind needed to carry out job tasks, previous experience in similar work, and compatibility with other employees. Most common of th<i considerations written in by farm operators is pirsonal honesty. Others they specify range from such general characteristics as attitude, physical appearance, health, and willingness to learn, to factors that arc more clearly job-specific, such as ability to understand instructions in English, possession of a driver’s license, and tolerance of bee stings. The classical basic standard is also on the list: “… is a walking body.” It is one thing to value a characteristic and another to determine whether applicants possess it. Systematic approaches to employee selection depend on information with which to rate applicants on criteria directly related to requirements of the job. Casual approaches arc not designed to sort workers carefully according to qualifications, so the information requirements–and the costs of meeting themfor such methods are less. How much information to obtain about job applicants, through which sources to get it, and in what order to tap the sources arc cost-benefit issues faced in every selection process. A combination of sources is needed to develop full information on criteria relevant to most jobs. The ability to follow written instructions, for example, may be established through completion of an application form, the knowledge and physical skill to correctly prune vines through a practical test or demonstration, the mathematical skill to calibrate chemical dilution through a written test, a willingness to work long and irregular hours through an interview,greenhouse bench top and abstinence from use of drugs through a medical exam. How accurate is the adage that farmers arc more careful choosing spark plugs to put in their tractors than drivers to put on them?

To what extent is information from various sources used in deciding whether workers have the qualifications that farm employers want? The most heavily used sources, utilized by about 90 percent of respondents, are the direct interview and comments from foremen or other employees Hable E-7; response that source is used “a lot” is classified in the table as “major”; responses that source is used “some” or “a little” are classified “minor”. Despite its widespread use, the traditional interview is notoriously fertile ground for interviewer biases to reduce the validity of results for forecasting future job performance, but interviews that are carefully structured can yield quite objective evaluations. The present survey provides no basis for knowing how respondents design this or any of the other selection information tools. Written applications can deliver large amounts of information abou1 workers cheaply and in reasonably comparable form, and statements on applications are often useful to discuss in subsequent interviews. The use of this tool in agriculture appears to be limited, however, by the non-cognitive nature of much production work, substantial illiteracy in the farm workforce, traditions of casual infield hiring, and delegation of considerable screening authority to foremen. Only half of the farm operators overall use written applications. Rates of use are significantly higher in larger firms. Although nearly all farmers say that they consider skills in hiring for production jobs, less than two thirds report using short-term trials or practical tests to assess applicants and one-third use written tests. Farmers fluent in the language spoken by most of their workers imply or directly suggest that staff of the service should more carefully assess workers before referring them to prospective employers. Although objective information about applicant skills and knowledge would be used by a broad range of survey respondents, more than a third say that they would never call for such assessment, even if provided free of user fees . A like proportion , however, would be Inclined to use this kind of service in more than half of their hires into production jobs. Anticipated utilization is generally greater among farms with larger payrolls and in vegetable and nut businesses.In today’s agricultural workplace, at least as much as in other types, personnel management is fraught with interpersonal, technical, and legal complexities. Few farm operators go it alone. Most either hire or contract with professionals to assist in parts of the personnel function. The professionals that most farmers depend on are payroll accountants or bookkeepers and attorneys . Services of employee and supervisory trainers, personnel specialists and consuItants. employee relations assistants, and recruiters are also used by substantial shares of survey respondents .

Nearly all of the attorneys and most of the personnel specialists arc contracted as outside providers, while professionals of other types are mainly hired as farm staff. The propensity to retain each type is significantly greater among farms with larger payrolls and among those in which production employees are or ever have ever been represented by a union.Good job performance by workers depends on their knowing what they arc expected to do, having the ability to do it, and making efforts to apply that ability. None of these elements is sufficient by itself to get anything done. Farm managers communicate their expectations to workers before and during the period of employment. Uyproviding information, explicit training, and on-the-job learning situations, they may also help develop workers’ abilities. Traditionally orientation to farm jobs has been handled in casual style, often by crew supervisors who merely introduce a new hire to crew members and the work flow. Workers entering farm businesses through kinship and friendship networks arrive somewhat oriented to their jobs and working conditions. For these newcomers espetially, continuing orientation and integration into the workforce tends to center on social and familial relationships. Frequently overlooked as a vehicle for worker onentation arc the recruitment and selection processes, which are mostly geared to providling information for the farm employer to use in hiring decisions. Through procedural steps they undergo on the way to getting hired, applicants too acquire informatio nand form impressions that affect their decisions about how to perform on the job and whether to accept an employment offer in the first place. Indeed, people may select themselves out of the running for lack of interest or qualification, based on what they comprehend in advance about the job content and performance expectations. No matter how thorough the selection and orientation of workers, there is always more to get across about what to do, why to do it, and how to do it, as well as about the terms of employment under which the work is to be done. Some employee training, such as in injury and illness prevention,cannabis dry rack is specifically required by law, but most comes about Simply as a matter of operational necessity. Even where workers are selected for their previously demonstrated proficiency in certain tasks, managers have to put some time into describing and encouraging adherence to their farms’ performance standards.

Where hiring is based more on such “character attributes” as honesty, loyalty, integrity, responsibility, and learning potential, the employer takes on the more basic chore of helping workers to develop specific skills on the job. Some managers find further that they have to ease workers out of Objectionable techniques or work habits that were learned elsewhere. How do farm employees get to know about their jobs, the farm operation, personnel policies, and others’ perceptions of their work? Workers in the vast majority of respondent businesses obtain their information through verbal instructions from supervisors and tailgate meetings at the work site . Other means by which farm operators inform workers are: written rules that are either posted or distributed , group orientations , staff meetings held indoors , employee handbooks , written job descriptions , structured performance evaluations , video tapes C7 percent, and audio tapes . These latter eight vehicles, requiring advance preparation and characteristic of structured personnel management, are all significantly more common in the larger farm businesses. Sale proprietorships, even within the large-size groups, are much less likely than farms organized in other forms to use written job descriptions, and non-family partnerships are more likely to have written work rules. Direct communications are integral to hiring and training employees, assigning and coordinating work, and handling all other aspects of employee relations. Hardly any farmers tum biological material and processes into marketable product by themselves, and many do not even themselves supervise all the hired employees who perform production work. A language difference between employer and production worker, if not sheer organizational size, may necessitate an intermediate level of supervisory employees.Spanish is normally spoken by most production workers on more than three-quarters of California farms <table F-3). English is the only other language mainly used in more than a handful of farm businesses, most commonly in the Sacramento Valley and “other” counties regions. Very few respondents report that workers speak either Mixtec, Portuguese, or Punjabi , and not one specifies Hmong or Tagalog. Predictably, farmers arc most fluent in their employees’ main language in regions where English is more commonly spoken by workers, but many arc also able to function to some degree in Spanish, In nearly two-thirds of all farm businesses, and in a majority of even those where most workers speak Spanish, the operator is able to communicate instructions in the workers’ main language. Farmers unable to speak adequately with workers usually communicate through hired foremen or crew leaders . Some are aided by non-supervisory workers, farmer family members, friends, and neighbors.Understanding the work assigned and having the ability to perform it do not get tasks done unless accompanied by an exertion of effort. And when other things arc equal, peopkput effort into what brings them more pay. Just because money is a valued incentive, however, docs not mean that it always stimulates effort in the directions that employers want. The ways in which farmers structure and administer compensation have great influence on what employees expect to gain from different kinds of effort and hence how they apply themselves. Workers respond to not only the wage rate bu/also the pay basis, generally units of production or units of time for which a compensation system pays. “Incentive pay” directly links current compensation to desired performance. Piecework, compensated at a fixed cash multiple of units produced, is the most common but by no means the only incentive plan in agriculture, Several problems limit its use. Before the work begins in earnest, rate-setting games may interfere with farmer-worker relations. Once regular work does begin, the rush to produce in quantity, which pays, can lead to the neglect of quality, which does not. In cohesive work groups, fear of rates slipping or slower performers losing their jobs may defeat the system, as workers informally establish and work toward a “safe” level of individual production that is well below their average capacity. Where there is no such brake on the incentive effect of piece rates, there is sometimes concern about the effects of overexertion on health and safety as well as on longer term performance. The technology of many farm operations precludes the use of such incentive pay. lt might have been appropriate, for instance, to pay milkers by the gallon in an era of smaller dairies and no machines. The volume of milk production today, though, is less directly attributable to the efforts of designated milkers. Mechanized and even machine-aided harvest systems in field crops and vegetables give workers much less control 01 work pace and hence output quantity than they had under lormer methods. In general, output-based incentive plans are better suited where: output is easily measurable, employees have a high degree 01 control over output, delays in work process are largely caused by humans, the technology is stable, and workers on individual plans or crews on group plans work independently 01 others. On what basis do larmers calculate pay lor most of their production employees?

The implemented trackers were evaluated for their precision and computing time

Due to the difficulties described in the current CV approaches, tracking pig activity is a challenging task without considerable labor efforts. The objective of this paper is to develop a semi-supervised pipeline, Virtual Tag , to automate long-term tracking of group-housed pigs. In this pipeline, successful tracking algorithms are implemented. They include Sparse Optical Flow proposed by Lucas and Kanade , multiple instance learning , and channel and spatial reliability that learn representatives from the object of interest and to find the similar image region in the next input video frame. These algorithms are lightweight and require no specific computing resources such as graphics processing units . The implemented tracker substantially reduce efforts in labeling pig positions for every single frame. To start tracking, users can either assign initial positions, or VTag can predict the positions based on their motion, which is anticipated to be effective features under different monitoring environments. We validated VTag by four three-hundred-frame videos collected from our farming trials, and the benchmark test is performed to compare the performance and detected frames per second of the implemented trackers and other state-of-the-art models, such as YOLOv5 and Mask R-CNN . In addition, VTag is released as a friendly software tool in both a graphical user interface and a Python library, allowing users to freely utilize the labeled data for their following research. Therefore, neither hard-coded features selected by human experts nor large training datasets labeled from a massive manual work are required in our pipeline.All animal experiments were approved and carried out in accordance with the Virginia Tech Institutional Animal Care and Use Committee under protocol #19-182. The demonstrated video recordings were obtained from ,vertical grow racks which reported the image-based live body weight prediction of non-restrained grower pigs. The pigs entered the trial at 5 wk post-weaning. The imaging system was built with a laptop-controlled camera that captured RGB and depth videos with resolution of 848 × 480 pixels.

The camera was installed at a height of 2.25 m perpendicularly to the floor in each 5 × 7 ft pen, where pigs can freely move and walk during the entire recording. In each day, each monitored pen was recorded in a three-hundred frame video at a rate of 6 frames per second. Raw videos were saved in Robot Operating System bag video format, and the decoder Intel RealSense Viewer was applied to obtain sequential image fles as the input data. In this study, only RGB converted grayscale images were used, and depth and color information were excluded from the pipeline. Each video clip had 300 time frames. There were four video clips being evaluated for the performance of the presented pipeline: 3 clips contain 1, 2, and 3 pigs , respectively. The last clip also contains 2 pigs, but more motion was observed.To evaluate the precision, we manually labeled the central positions of each pig body as the ground truths. The precision error was determined by the Euclidean distance between the ground truth and the centroid of the predicted bounding box. To make the results comparable with other studies, the error was standardized by being divided by the diagonal distance of the video frame ranging from 0 to 1. In addition, as the tracking process may be unsuccessful when the similarity of two consecutive frames is low, human supervision is needed to provide new tracking positions to resume tracking. Hence, we also evaluated the number of supervision is needed to complete tracking the 300 frames in each dataset. To evaluate the computing time, the elapsed time to track one single frame is measured for 100 iterations. The time is presented in FPS by inverting the observed elapsed time. In addition to the implemented trackers, the object detection models, YOLOv5 and Mask R-CNN, pre-trained by the COCO dataset are also included in the evaluation of computation time. It can help explore the possibility of adapting these pre-trained deep learning models in the pig tracking tasks.

The evaluation was run on a personal laptop, MacBook Pro with Apple M1 Max chip, 10 CPU cores, and 32 GB RAM. The GPU resources were not utilized during the evaluation.The VTag pipeline is released as a Python software and can be accessed by a GUI or an interactive Python session. There are 3 components that users can interact with in the GUI: the video previewer, the playback controller, and the configuration. The preview shows the video overlayed by the tracking results, which are presented by a centroid and its tracking window area. Different tracking points are colored differently to show pig entities. The video can be played, paused, and traversed to any video frame by interacting with the playback controller . Each frame in the progress bar is colored in a gradient scale from yellow to blue, showing the tracking errors estimated from the implemented tracker. In the configuration panel , parameters needed for the tracking task are tunable. In the panel, users can load a directory containing the video to start the tracking tasks, adjust the number of tracked objects and tracking size, and optimize the quality for displaying the tracking results. If users need to work with their own analysis in an interactive programming session, users can load VTag in Python as a library. The library has commands available that correspond to all the actions in the VTag GUI. In sum, VTag provides a friendly platform to annotate video data and generate informative farming guidance for pig activity.The precision evaluation is presented in Figure 3, the standardized errors over frames were plotted in boxplots. Every 0.1 of the standardized error is 26.29 cm in the presented datasets. The colors represent different supervisions. For example, the results shown in red are evaluated after 8 times of human supervision.

With adequate human supervision, all trackers can precisely track pig activity with errors less than 22.82 cm in all the 4 datasets. In particular, the tracker LK can complete the tasks without any resuming supervision with the median errors of 18.03 and 13.81 cm for the datasets of one-pig and three-pig, respectively. The tracker CSRT performed similarly well with only one additional supervision with the median error of 16.3 cm in the studied datasets except the dataset of two-pig . Among the studied trackers, MIL has similar precision but requires more human supervision than others in all the dataset. It is noted that the number of tracked objects is not a major limiting factor when it comes to tracking precision. In this study, more supervision is needed when the objects are found to move rapidly and create blurry image features. When the pigs move rapidly, the input video with low FPS had latencies to display object positions timely. In the 2-pig dataset although with similar precision, 7, 5, and 13 supervisions were needed to complete tracking the 300 frames for the 3 trackers, respectively. The computing time is presented by FPS, which indicates how many frames the tracker can process per second . As results, LK tracked averaged FPS of 900 and showed out performance in computing speed to other trackers by more than 100 folds. CSRT is the second fast tracker with a performance ranging from 9.9 FPS to 60.81 FPS in the tasks of tracking different number of pigs. MIL is found to be the slowest tracker, with as low FPS as 1.8 FPS when it tracked six pigs. It is also found that for the trackers CSRT and MIL, the numbers of tracked objects affect the tracking speed non-linearly. Additionally, the pretrained object detection models are evaluated in this study as well. Without enabling GPU resources, both models predict the studied videos slower than the presented trackers. Only 4 FPS and 0.17 FPS are processed by YOLOv5 and Mask RCNN, respectively.The distance between studied subjects implies 2 types of general social interactions: separated or engaged. When the subjects engage closely, the distance values are low during the period of time frames. Otherwise,indoor grow lights shelves subjects are separated apart without much interaction. A line chart of the distance against the 300 time frames was visualized to monitor such patterns, showing 4 peaks and 4 valley values from the 2-pig data . To examine whether the distance is an effective indicator for the interactions, video frames with peak and valley values were displayed. Consequently, in the frames with peak values, interaction was observed among pigs, and they were observed staying in 2 different corners of the pen at the examined time frame. On the other hand, in the frame with valley values, social interactions were observed for all inspected frames. Pigs were in the status of in-taking feeds alongside or chasing each other. From the examined 300 frames, the estimated distance between pigs is an accurate indicator to filter time frames where social interactions may occur. By knowing the tracks of each pig, pixel movements per time frame were studied to monitor the activities individually. In the presented data, 2 studied pigs were denoted as “Pig_1” and “Pig_2”. The median movement of Pig_1 and Pig_2 is 21.1 and 21.98 pixels per frame, which show no significant difference in overall activity . However, individual-specific temporal pattern can be discovered by dissecting the activity at certain time frames.

For example, during the first 50 frames, Pig_2 was much more active, the difference between Pig_1 and Pig_2 was especially revealed in those peak movements. Moreover, after the 50th frame, Pig_2 continuously had greater changes of accumulated movements over Pig_1. The superiority was 1739.7 pixels at the 50th frame, and it was later expanded to 3612.9 pixels at the 250th frame . Finally, we inspected the synchronicity between pigs by comparing their movements per frame . A moderate correlation was observed in the studied data, which implied that the activity of each individual was not independent and were partially determined by its neighboring pig. In addition to monitoring the temporal activity, spatial patterns of pig movement can be informative for herd management. Heat maps generated from pixel-wise variation across all time frames provided insightful guide on what areas were visited most . In the one-pig data , middle-top and bottom-left regions have found to be the hot spots, which were the places to engage with neighboring pigs and the feeding area, respectively. Whereas in the 2-pig data , there was no clear spatial trend of the subject activity. Most corners of the pen were visited by both pigs except the central area.Continuously tracking pig activity from videos is an important initial step to monitor farming conditions in swine industry. Including animal diseases, welfare, and pen-scale social interactions, such complex monitoring tasks require detailed observation of pig activity. Many existing works have automated the tasks through the aid of CV technology but required massive human effort in preparing data sets to build an effective system. In contrast, this paper presented a semi-supervised pipeline, VTag, which does not require laborious work in setting up the training system. Solely relying on a top-view and grayscale video, VTag provides an efficient approach to continuously track the positions of group-housed pigs with an average error of 17.99 cm in the presented datasets. The results can serve as preliminary farming guidance to infer complex traits that used to require intensive labor resources. For example, by continuously tracking pig positions with VTag, individual-level activity per unit time and walking speed can be estimated. This is important information for the trait assessment of pig lameness, which can be potential indicators of fractures, lesions, and development disease , and diminishes welfare in pigs. Hence, effectively evaluating lameness allows farmers to control economic losses from losing pigs with poor body conditions . Another important monitoring task that can be improved with VTag is tail biting in pigs. Because tail biting is linked to stressful farming conditions and lower body weights , detecting the negative events at an early growing stage can be beneficial to both animal welfare and production. As the real-time pig positions are obtained automatically, the relative distance between individuals in the pen can be estimated. Behavioral researchers can use this information to filter a specific time range from an hour-long video: When the relative distance is low, it is more likely to observe tail-biting events.

Monocular vision has been used for guidance in orchards

In these operations plants grow in distinct rows and the wheels of the autonomous vehicles must drive only inside the space between rows. Examples include open field row crops ; orchards with trees/vines/shrubs and their support structures; greenhouses and indoor farms. Crop-relative auto-guidance is necessary in the situations described above. Researchers have used various sensors, such as onboard cameras and laser scanners to extract features from the crops themselves, and use them to localize the robot relative to the crop lines or trees rows in order to auto-steer. Crop-relative guidance in open fields and orchards is still more of a research endeavor rather than mature, commercial technology. Researchers have used monocular cameras in the visible or near infrared spectrum , or multiple spectra to segment crop rows from soil based on various color transformations and greenness indices that aimed at increasing segmentation robustness against variations in luminance due to lighting conditions. Recently, U-Nets , a version of Fully Convolutional Networks were used to segment straw rows in images in real-time . Other approaches do not rely on segmentation but rather exploit the a priori knowledge of the row spacing, either in the spatial frequency domain – using band pass filters to extract all rows at once – or in the image domain . An extension of this approach models the crop as a planar parallel texture. It does not identify crop rows perse, but computes the offset and heading of the robot with respect to the crop lines . Once candidate crop row pixels have been identified various methods have been used to fit lines through them. Linear regression has been used,vertical growing racks where the pixels participating are restricted to a window around the crop rows . Single line Hough transform has also been used per independent frame , or in combination with recursive filtering of successive frames .

In an effort to increase robustness, a pattern Hough transform was introduced that utilizes data from the entire image and computes all lines at once. Researchers have also used stereo vision for navigation. In an elevation map was generated and the maximum value of the cross-correlation of its profile with a cosine function was used to identify the target navigation point for the vehicle.Most reported work was based on monocular cameras, with limited use of stereo vision and 2D/3D lidars. One reason is that in early growth stages the crops can be small in surface and short in height; hence, height information is not always reliable. Given the increasing availability of real-time, low-cost 3D cameras, extensions of some of the above methods to combine visual and range data are conceivable and could improve robustness and performance in some situations. Also, given the diversity of crops, cropping systems and environments, it is possible that crop or application targeted algorithms can be tuned to perform better than ‘generic’ ones and selection of appropriate algorithm is done based on user input about the current operation. The generation of publicly available datasets with accompanying ground truth for crop lines would also help evaluate and compare approaches.Orchards rows are made of trees, vines or shrubs. If these plants are short and the auto-guided robot is tall enough to straddle them, the view of the sensing system will include several rows and the guidance problem will be very similar to crop-row relative guidance. When the plants are tall or the robot is small and cannot straddle the row, the view of the sensing system is limited to two tree rows when the robot travels inside an alley, or one row if it is traveling along an edge of the orchard. Multiple rows may be visible only when the robot is at a headland during an entrance or exit maneuver. In this situation the images captured by the sensing system look very different than between tree rows, and therefore the row-following sensing and guidance techniques cannot be used. The main approach is to detect the tree rows and compute geometrical lines in the robot’s coordinate frame and use them for guidance.

Robustness and accuracy are very important, because erroneous line calculations could cause the robot to drive into trees and cause damage to itself and the trees and orchard infrastructure. Although the problem seems well defined and structured, the following conditions present significant challenges: the presence of cover crops or weeds on the ground can make it difficult to discriminate based only on color; tall vegetation can hide tree trunks that are often used as target for row-detection systems; trunks from neighboring rows are often visible too; variability in illumination conditions during the day or nighttime operations , and environmental conditions affect sensing. Trees grow at different rates and may be pruned/hedged manually resulting in non-uniform tree row geometries. Also, there is a large variety in tree shapes, sizes and training systems, and orchard layouts, which makes it difficult to design ‘universal’ guidance algorithms that rely on specific features. For example, Figure 4a shows a recently established orchard with small trees right out from a nursery, where canopies are small and sparse; Figure 4b shows younger trellised pear trees; Figure 4c shows high density fruit-wall type trellised apple trees; Figure 4d shows old open-vase pear trees in winter; Figure 4e shows large, open-vase cling-peach trees; Figure 4f shows a row of table grape vines.In a tree trunk-based approach visual point features from tree trunks are tracked and a RANSAC algorithm selects a number of inlier points whose locations are reconstructed in 3D using wheel odometry and the vehicle kinematic model. Then, lines are fitted to the points and an Extended Kalman filter integrates the vanishing point with these lines to improve their estimate. In a sky-based approach is pursued, where the high contrast between tree canopies and the sky was used to extract the boundary of the portion of the sky visible from the camera, and from that the vehicle heading. In the image is segmented into classes such as terrain, trees and sky. Then, Hough transform is applied to extract the features required to define the desired central path for the robot. The fact that even young trees in commercial orchards extend much higher than the ground level has resulted in heavier use of ranging sensors for orchard guidance than what has been reported for row-crop guidance. In a 2D laser scanner was placed 70 cm above the ground, horizontally, and Hough transform was used to fit lines through the points sensed from trunks at the left and right of the robot. Line regression has also been used to fit lines and was combined with filtering to improve the robustness of line parameter estimation .

Line-based SLAM was also proposed to simultaneously estimate rows and localize the robot with respect to them . 3D lidar has also been used to get range measurements from the surroundings , given that 2D lidars can only scan at a certain height above the ground where tall vegetation or vigorous canopy growth may partially occlude or even hide trunks. In the point cloud of each lidar scan is registered with odometry and combined with recent previous ones in a single frame of reference. Then, the left and right line equations for tree rows are computed in a RANSAC algorithm operating on the entire point cloud,vertical grow room design and an Extended Kalman filter is used to improve the robustness of line parameter estimation. The lateral offsets of the fitted lines are refined further by using points from heights that correspond to trunks. Off the shelf, low-cost 3D cameras were used also to detect orchard floor and tree trunks . Random sampling and RANSAC were used to reduce the number of points and exclude outliers in the point cloud, and a plane was fitted to the data to extract the ground, whereas trees were detected by their shadows in the generated point cloud. Sensor fusion has also been reported for auto-guidance in orchards. In an autonomous multi-tractor system was presented that was used extensively in commercial citrus orchards for mowing and spraying operations. A precise orchard map was available depicting tree rows , fixed obstacles, roads and canals. An RTK GPS was the primarily guidance sensor for each autonomous tractor. However, tree growth inside orchard rows often necessitates that the robot deviate from pre-planned paths. A 3D lidar and high dynamic range color cameras were used to build a 3D occupancy grid, and a classifier differentiated between voxels with weeds and trees, thus keeping only voxels representing empty space and tree canopies. The row guidance algorithm used GPS to move towards the waypoint at the end of the row and the 3D grid to find the lateral offset that must be added to the original planned path to keep the tractor from running into trees on either side. Robust, accurate and repeatable turning at the end of a row using relative positioning information with respect to the trees is very difficult and has not been addressed adequately. A successful turn involves detecting the approach and the end of the current row, initiating and executing the turning maneuver, and detecting the entrance of the target row to terminate the turn and enter the next row. One approach is to introduce easily distinguishable artificial landmarks at the ends of tree rows . Landmarks can be used to create a map , detect the end of the current row, the entrance of the next row, and localize the robot during turning, using dead reckoning. In end-of-row detection utilized a 2D lidar, a camera and a tree-detection algorithm. Turning maneuvers were executed using dead reckoning based on wheel odometry. Dead reckoning with slip compensation has also been used .

Crop status and growth are governed by the interaction of plant genetics with the biotic and abiotic environment of the crop, which are shaped by uncontrolled environmental factors and agricultural management practices. The biotic environment consists of living organisms that affect the plant, such as neighboring plants of the same crop or antagonistic plants , bacteria, fungi, viruses, insect and animal pests, etc. The abiotic environment includes all nonliving entities affecting the plant, i.e., surrounding air, soil, water and energy . The environment can cause biotic or abiotic crop physiological stresses, i.e., alterations in plant physiology that have negative impact on plant health and consequently yield, or quality. Examples include plant stress due to fungal diseases, water stress due to deficit irrigation, reduced yields due to weeds or drought, crop damage due to excessive temperatures, intense sunlight, etc. The environment and potential stressors affect strongly crop physiological processes and status, which are expressed through the plant’s biochemical and biophysical properties, some of which can be measured directly or indirectly. Examples of such biochemical properties are the number and types of volatile organic compounds emitted from leaves . Examples of biophysical properties include leaf properties such as chlorophyll content, relative water content and water potential, stomatal conductance, nitrogen content, as well as canopy structure properties. Canopy structure is defined as “the organization in space and time, including the position, extent, quantity, type and connectivity, of the above ground components of vegetation” . Components can be vegetative such as leaves, stems and branches, or reproductive, i.e., flowers and fruits. Canopy structure properties can be based on individual components , on indices that characterize ensembles of components or indices that characterize entire plants, such as a canopy’s leaf area index. Finally, a special property, that of plant ‘species’ is of particular importance because it is used to distinguish crops from weeds and classify weed species for appropriate treatment. Estimation of crop and environmental biophysical and biochemical properties is based on measurements that can be made through contact or remote sensing. Contact measurements are mostly associated with the assessment of soil physical and chemical properties and involve soil penetration and measurement of quantities like electrical conductivity or resistance . Contact sensing for crops has been very limited so far , partly due to plant tissue sensitivity and the difficulties of robotic manipulation .

Including sub-disdrict fixed effects increases the magnitude to 19 percentage points

T2 shows no change by 2011 , but a large reduction by 2012 . Panel shows the association with fine particulate matter. PM2.5 concentration did not change significantly in the control group between baseline and follow-up. Households in T1 show significant reduction in average PM2.5 concentration at the first and second follow-ups. Households in T2 show no reduction in PM2.5 concentration by the first follow-up, but a significant reduction in mean PM2.5 concentration by the second follow-up. This reduction is not statistically different from the average reduction experienced by households in T1. This graph shows three striking facts. First, Both PM2.5 and kerosene expenditure change when electrification status changes. Conversely, none changes if electrification status doesn’t change . Second, the average changes among households in T2 are similar to those experienced by households in T1. Third, the new levels of kerosene consumption and PM2.5 observed for T1 in 2011 are maintained in 2012. The results are presented in Table 3, briefly discussed above. Connection to the grid is associated with 53% reduction in PM2.5 concentration between 5pm and 7am. This estimate is strongly significant. The point estimate is slightly larger in the evenings , when PM2.5 concentrations are 300 µg/m3 . The estimate for late night is also high, at 51%, but PM2.5 concentration is 140 µg/m3 , around half of the evening period. The reduction in PM2.5 in the early mornings is 42%, still large but slightly lower than the other subperiods. Average PM2.5 concentration in this subperiod is the highest, at 350 µg/m3 , which could indicate cooking breakfast. As we discussed earlier,cannabis drying system cooking fuel did not change with electrification. Using the data for T2 and T3 to test for differential pre-treatment trends in PM2.5 and the 2010 EHEIPCER wave to test for differential pre-treatment trends in expenditure in kerosene or candles, use of wood, candles, we cannot reject the null hypothesis of parallel pre-treatment trends in any of the tests we performed.This subsection analyzes changes in traditional fuel use induced by electrification and suggests kerosene as the main channel through which electrification affected overnight PM2.5 concentration.

Table 6 reports the effects of electrification on energy use. Our findings conform with the stylized fact that newly electrified households use electricity first for illumination. Electrification reduces the probability of using kerosene by 60 percentage points by round 2 . The reduction by round 3 is smaller, 22 percentage points , and by round 4 is larger again, at 43 percentage points . Monthly expenditure in kerosene decreased accordingly, by $3.57 at round 2, $2.07 at round 3 and $1.94 at round 4. The use of kerosene in kWh per month also decreased with electrification, by between 50-80% of the baseline value by rounds 2, 3, and 4, respectively. Other substitutes to electricity, like candles and car battery show no significant changes, although in some cases the standard errors are too large to reject sizable effects. These sources are less important in the household’s energy budget than kerosene, so detecting an effect would require larger sample sizes. As mentioned in the preceding section, similar patterns arise in the non-experimental sample. Next, we examine whether changes in cooking practices could have also generated the observed changes in overnight PM2.5 concentration. This is unlikely since the use of wood for cooking was around 85% and did not vary during the study period. As we saw in Table 1, 60% of the population agreed that cooking with electricity was very expensive. The bottom panels of Table 6 show that electrification did not lead to statistically significant changes neither in the use of wood for cooking nor in the probability of cooking outdoors. The coefficient on electrification in the use of wood regression for round 2 is larger than desirable, but the coefficients in rounds 3 and 4 are close to zero. Similarly, the coefficient on electrification corresponding the regression on cooking outdoors in round 4 is non-significant but large, while the coefficients for rounds 2 and 3 are close to zero. Although we cannot reject moderate changes in two of the six regressions on cooking practices, it seems most of the variation in overnight PM2.5 concentration is due to the large and statistically significant changes in kerosene consumption. Lower respiratory infections cause 2.8 million deaths globally in 2010 and thus they constitute a major public health concern. In this subsection we show that the reductions in overnight PM2.5 concentration generated by household electrification had sizable effects on respiratory infections among children under six years old. The experimental sample includes 380 children in this age-range.

Despite this relatively small sample size, there are large and statistically significant reductions in the incidence of acute respiratory infections among children. The dependent variable indicates whether the child had an episode of acute respiratory infection in the four weeks prior to the survey . When the explanatory variables are voucher, round, and their interactions, we find that vouchers led to a reduction of 16 percentage points at round 3. Adding baseline characteristics and the number of vouchers within 100m results in reductions of 18 and 17 percentage points. In all cases the reductions are significant at the 90%. These figures are large, and even more impressive when compared to the baseline since they represent reductions of between 37 to 44 percent of the mean incidence among non-recipients at round 3. The coefficient on voucher at round 4 is positive across all specifications, implying increases in ARI incidence of 8 to 11 percentage points among voucher recipients, and it is significant at the 90% in the first specification. Moreover, in no specification the null hypothesis that the coefficients on voucher in both rounds have the same magnitude can be rejected. This may initially seem a puzzle but it merely reflects that the electrification rate among non-recipients caught up with that of voucher recipients by round 4. It is worth noting that it is not the case that ARIs bounced back up to their original levels, since ARI incidence reduced from 44% to 10% between rounds 3 and 4. So, consistent with the analysis of PM2.5concentration, this shows that the effects of electrification are similar irrespective of whether a household received a voucher. The time allocation data was collected for up to four household members: the household head, his or her spouse, and up to two school-age children. This allows estimating PM2.5 exposure for four “synthetic individuals”: adult female, adult male, female child, and male child. Table 8 presents average time allocation in four type of activities for each of our synthetic individuals. The male and female heads report 8.9 hours of sleep per day, while the children report 9.5-10 hours of sleep per day. Time at home during the evening is similar for all members . The starkest differences are observed in time spent in the kitchen and time spent outside the home. While female head reports 2.5 hours per day in the kitchen, the male head reports spending an average of just five minutes. On the other hand, the female head reports spending an average of 2.7 hours outside the home,cannabis vertical farming while the male head reports 7.8 hours . The differences in time allocation that arise from this analysis already suggest that adult females are more exposed to PM2.5 since they spend considerably more time in the kitchen than any other household member. On the other hand, males spend almost one third of the time outside the home.

The main activity is farming and walking to and from the farm, where it can be safely assumed that exposure to PM2.5 is negligible. Next, we make explicit the assumptions about the PM2.5 concentration in the environments where these activities were likely conducted. As shown earlier, average PM2.5 concentration in the living room during the evenings is 0.40 mg/m3 . We take this as representative of any room in the household, except the kitchen, between 1700 hours in the evening and 0700 the next morning. Based on the sub-sample of households for which we have 3-day measurements, we estimate the average PM2.5 concentration in the living room during daytime to be 0.26 mg/m3 . We take this as representative of the rooms in the household during daytime, again with the exception of the kitchen. Since we did not collect data on PM2.5 concentration in the kitchen, we use 0.90 mg/m3 , which corresponds to average PM2.5 in the kitchen in Guatemalan households . This figure seems an adequate assumption in our context since it corresponds to a neighboring region where households also rely of fuel wood for cooking. This makes our exposure estimates adequate for households that rely on wood for cooking, and even conservative given that its not uncommon to find cases where the average concentration is above 2.0 mg/m3 . We assume household members will not be exposed to PM2.5 whenever they are not home. This assumption seems not to be too restrictive for the population in our study setting, since most of the time outside the home is spent in outdoors activities like farming, and very little time is spent conducting activities outside the home that suggest exposure to PM2.5 .The third and final component in is the inhalation rate. Since inhalation rate depends on age, we estimated it for the sample averages: 43 for the female head, 47 for the male head, 11 for the female child, and 13 for the male child. Air inhalation rates per activity are based on the EPA Exposures Handbook . Most activities conducted at home can be classified as “light activity tasks” by the EPA. Light activities include cooking, washing dishes, ironing, watching TV, doing desk work, writing and typing, and walking at a speed of up to 2.5 mph . The average inhalation rate for these activities is 0.78 m3/hour, while the average air inhalation rate while sleeping is 0.30 m3/hour, again similiar for the four synthetic individuals. The inhalation rate for activities conducted outside the home will vary greatly, depending on the intensity of these activities. For instance, walking to work could be classified as light or medium intensity, depending on the speed at which the person is walking. Farming, on the other hand, could be classified as medium to high intensity, but if lunch breaks would be light activity. However, the assumption made earlier about PM2.5 concentration being zero outside the home makes the inhalation rates of these activities irrelevant for total exposure. With these three components we estimated exposure rates for the four synthetic individuals. Estimated exposure measures are highest for the female head, at 5.68 mg/day, and lowest for the male head, at 3.20 mg/day. The exposure measures for children lie in between, with females 4.23 mg of PM2.5 per day males to 3.72 mg/day. Taken plainly as units of PM2.5, these concentrations are equivalent to 8.0 cigarettes a month for the male head, 14.2 for the female head, 10.6 for the female child, and 9.3 for the male child31. The scientific evidence is yet inconclusive as to whether generated by PM2.5 cigarette is worse or not than that generated by kerosene combustion. The changes in exposure are large for all members , but these gains are unequally distributed across household members. The male head benefits the most, with a reduction in exposure of 59%, while the female head benefits the least, with a reduction of 33%. As pointed above, these differences owe to females spending more time than males in the kitchen, where pollutant concentration is highest, while males spend more time than females outside the home, where pollutant concentration is lowest. To date, there are no dose-response functions linking exposure to PM2.5 from kerosene combustion to health outcomes. However, Pope III et al. presents an estimate of a dose-response function linking PM2.5 from first- and second-hand tobacco smoking to lung cancer and cardiovascular diseases. In Panel of Table 8 we present the relative risks that would be associated to the exposure levels found in Panel if the health effects of PM2.5 from kerosene combustion were similar to those from tobacco smoking.

The genetic control underlying these PUE mechanisms is covered in the subsequent section

Increased production of lateral roots, adventitious roots and root hairs all increase root surface area, and thus will increase P acquisition from the water and sediment and are important traits for PUE in watercress. In addition, the root cap can account for 20% of the phosphate absorbed by the roots of Arabidopsis. Therefore, increasing the number of roots increases the number of root tips and the number of these “hot spots” for phosphate acquisition.Plants are reliant on phosphate transporters to acquire P from the environment and transport P between tissues, and this includes for aquatic plants. The PHT1 family is the most widely studied group of P transporters and is primarily responsible for P uptake but also has a role for P transport between tissues. A broad range of expression patterns are associated with different PHT1 genes but generally, higher expression of PHT1 genes is associated with improved shoot biomass accumulation and P tolerance . Watercress with higher PHT1 expression may result in improved biomass accumulation in P deficient water, but this has yet to be tested. Additional traits that are important in other crops are organic acid exudation and phosphatase activity. Since these control release of P from organic forms in the soil, they are less relevant to watercress cultivation where P released from bound sources would be rapidly lost to the watercourse. However, phosphatases that remobilise P from intracellular sources have been identified in Arabidopsis so similar phosphatases could enhance internal P utilisation in watercress.Alongside phosphate acquisition, PUE also refers to more efficient P utilisation associated with re-translocation and recycling of stored P,indoor grow facility that relies on effective P transportation within the plant, P scavenging, and use of alternate biochemical pathways that bypass P use.

Re-translocation between plant tissues is governed by transporters such as PHT transporters and PHO transporters. Unlike, PHT transporters which regulate P acquisition too, PHO transporters are solely responsible for P transport into vascular tissues and cells. Alternative P use strategies includes substituting phospholipids in cell walls with sulfolipids and galactolipids. Several enzymes in the glycolytic pathway depend on P so bypass enzymes such as pyrophosphatedependent phosphofructokinase , phosphoenolpyruvate carboxylase and pyruvate phosphate dikinase can be recruited to use pyrophosphate for a P donor and conserve limited ATP pools. Several studies have reported increased PEPC activity under P deprivation. The mitochrondrial electron transport chain responds by utilising non-phosphorylative pathways. Acid phosphatases in intracellular spaces or present in the apoplast can increase P availability by remobilising P from senescent tissues and the extracellular matrix. Both aspects of PUE rely on accurate sensing of the P state within the plant and external environment to alter global gene expression and ensure appropriate responses to upregulate P uptake and P use pathways.QTL for overall PUE metrics as well as QTL for more specific architectural root traits associated with low P tolerance have been identified in several economically important crops including soybean, soybean , rice , maize and common bean. RSA is extremely plastic, subject to effects of hormone signalling, environmental stimuli and under the control of several genes so elucidating these QTL is challenging. Studies on other Brassicaceae species are likely of most genetic relevance for QTL mapping in watercress, however QTL associated with other species such as soybean, rice, sorghum and wheat are summarised in Table 1. P-starved Arabidopsis exhibit longer root hairs and higher root hair density, decreased primary root length and increased lateral root density.

Three QTL, were identified which explained 52% of the variance in primary root length. In rapeseed primary root length decreases, lateral root length and density increases with declining P concentration. Several QTL are associated with these changes and many co-locate with QTL for root traits in Arabidopsis. A more recent study used over 13 000 SNP markers to construct a genetic linkage map in rapeseed, where 131 QTL were identified in total across different growth systems and P availabilities. However, only four QTL were common to all conditions, demonstrating strong environmental effects determining these QTL. To date, there is no published literature on QTL associated with aerenchyma formation under low P in any plant species and no studies exist on QTL mapping for root traits in watercress. Identification of QTL and markers associated with PUE could accelerate breeding for nutrient use and reduce the environmental impact associated with watercress cultivation.Genes involved in transcriptional control are multifunctional under P deprivation; some have overlapping roles in RSA development, P signalling and P utilisation. They are discussed together here despite partial involvement in P utilisation. PHR1 and PHL1 code for transcription factors that play critical roles in the control of P starvation responses. PHR1 mediates expression of the microRNA miR399 which modulates the PHO2 gene, responsible for P allocation between roots and shoots and affects expression of other PSR genes such as PHT transporters . SPX transcription factors are important negative regulators of PSR via repression of PHR . The roles of several other transcription factor genes on RSA and other regulatory elements are summarised in Table 2 and Figure 3. Auxin, sugars and other hormones such as cytokinins, ethylene, abscisic acid , giberellins and strigolactones are implicated in phosphate-induced determination of RSA so genes involved in these pathways may be significant candidates. Under low P, auxin levels increase in root hair zones and root tips.

Auxin mutants such as taa1 and aux1 have impaired root hair growth in low P. Expression of the Arabidopsis auxin receptor gene TIR1 increases under low P availability which results in increased sensitivity to auxin and production of lateral roots. Mutants in auxin-inducible transcription factors also have disrupted root hair responses under low P. ROOT HAIR DEFECTIVE 6- LIKE-2 and ROOT HAIR DEFECTIVE 6-LIKE-4 are responsive to P deficiency and promote root hair initiation and elongation. ARF19 is a key transcription factor promoting auxin-dependent root hair elongation in response to low P . HPS1 is involved in regulating the sucrose transporter SUC2 and hps1 mutants exhibit significant P-starvation responses under P-sufficient conditions. Plants with impaired cytokinin receptors CRE1 and AHK3 show increased sugar sensitivity and increased expression of P-starvation genes. ETHYLENE RESPONSE FACTOR070 is a transcription factor critical for root development under P starvation. Though no studies exist for P-associated gene expression changes in watercress, Müller et al. used RNA sequencing approaches to identify responses to submergence in watercress and found several ABA biosynthesis and catabolism genes associated with stem elongation. This study provides a model for using transcriptomic approaches to explore hormone-induced morphological changes in watercress. For P acquisition, the PHT gene family controlling P transport provides several candidate genes. In Arabidopsis, the PHT genes that encode phosphate transporters responsible for transport of P anions are well characterised and are grouped into four families . PHT proteins other than PHT1 are involved in the uptake, distribution and remobilisation of P within the plant, however, PHT1 in the plasma membrane is the most important. Phosphate stress induces expression of these genes. However,indoor grow rack the use of PHT transporters in plant breeding has been limited by P toxicity and other side effects of unbalanced P regulation associated with the over expression of some transporter genes. For example, OsPHT1;9 and OsPHT1;10 over expressing rice plants have reduced biomass under high phosphate compared to wild-type plants. Accessory proteins, encoded for by genes like PHOSPHATE TRANSPORTER TRAFFIC FACILITATOR , are also important for proper functioning of P transporter genes. Homologs of PHT1 transporter genes, transcriptional factors including the SPX gene family, and genes involved in RSA determination such as PDR2 and LPR1/2 could be candidate genes for improving phosphate acquisition in watercress, but these genes have yet to be identified in aquatic crops.The transcriptional regulation of PUE is complex: there is some overlap with genes involved in both phosphate acquisition and phosphate utilisation, such as the global transcriptional regulation by PHR1 and PHL1.

Here we target genes primarily involved in utilisation, including those responsible for P transport within the plant, alternate metabolic pathways, and internal Pscavenging. Using an Arabidopsis Affymetrix gene chip, changes in global gene expression have been analysed in response to P deprivation. The expression of 612 genes was induced and 254 genes suppressed including upregulation of phosphate transporters such as PHT1 genes and PHO1;H1. Genes involved in protein biosynthesis were downregulated during deficiency, likely representing P recycling strategies. PHT transporters also play a role in P utilisation through re-translocation of P within the plant. Five of the 13 maize PHT1 genes are induced in other tissues such as leaves, anthers, pollen and seeds, suggesting PHT1 involvement in diverse processes such as rootto-shoot distribution. PHO1 is another central element responsible for P homeostasis and transport. Pho1 mutants exhibit P deficiency in the shoots due to lack of P loading into the xylem vessels . Phosphatases are important for remobilisation of fixed P. Eleven genes encoding different purple acid phosphatases were reported to be upregulated under P starvation in Arabidopsis . The Arabidopsis genome encodes 29 purple acid phosphatases, some of which are excreted into the soil, such as PAP12 and PAP26. Only phosphatase activity within the plant is relevant to watercress breeding: in a f lowing water system, any P made available around the roots by secreted phosphatases would rapidly wash away. As well as being a major secreted phosphatase, PAP26 is regarded as the predominant intracellular acid phosphatase in Arabidopsis and is upregulated two-fold under Pdeficiency. PAP26 functions in PUE by scavenging P from intracellular and extracellular P-ester pools, to increase P availability in the plant. Homologs of PAP26 should be investigated in watercress. Plants also respond to P starvation by utilising alternative metabolic pathways. Genes involved in lipid metabolism and biosynthesis represent the largest group of core PSI genes in Arabidopsis, demonstrating their importance in PUE under P starvation. Three genes encode “plant-type” PEPC enzymes in Arabidopsis . PPC1 is expressed in roots and f lowers, PPC2 in all organs and PPC3 in only roots . PEPC activity is affected by phosphorylation by PPCK , thus PPCK1 and PPCK2 genes are additional important components for P-bypassing. Membrane phospholipids constitute approximately 20% of the total P in the leaves of P-sufficient plants. This represents a large pool of P that can be remobilised. 7% of the P-responsive genes found by Misson et al. were involved in lipid biosynthesis pathways in Arabidopsis. This includes the genes MGD2 and MGD3 whose expression changed 11-fold and 48- fold under P deficiency, respectively. These genes encode major enzymes for galactolipid biosynthesis and are involved in replacing phospholipids in cell membranes with non-phosphorus lipids such as galactolipid digalactosyldiacylglycerol. PECP1 is involved in the liberation of P from phospholipids and is upregulated under P deprivation, with up to 1785-fold increases in expression reported in roots. PSR2 encodes a phosphatase involved in galactolipid biosynthesis and whose expression increases 174-fold in P deprived seedlings. Both PECP1 and PSR2 have similar roles in the dephosphorylation of phosphocholine in the galactolipid synthesis pathway. However, despite their massive upregulation, it has been observed that inactivation of PECP1 and PSR2 does not alter plant growth or plant P content under P-deprivation so PCho is not likely a major source of P under limiting conditions. PLDζ1 and PLDζ2 encode phospholipases D zeta 1 and 2 that hydrolyse major phospholipids such as phosphatidylcholine which yields phosphatidic acid and PA phosphatase and releases DAG and P. Phospholipids can also be replaced by sulfolipids. SQD2 is the primary gene in this pathway and encodes an enzyme that catalyses the final step in the sulfolipid biosynthesis. GDPD1 is involved in the formation of glycerol-3- phosphate from phospholipid products , that can be dephosphorylated to release P. Homologs of PHT1 genes responsible for P redistribution, within the plant, genes involved in P scavenging , genes implemented in metabolic pathways that bypass P use including galactolipid biosynthetic pathways and those involved in sulfolipid biosynthesis could be candidate genes for improving phosphate utilisation in watercress.Watercress root research is virtually completely absent in the literature, with no studies on root responses to phosphate availability. Nevertheless, the finite nature of rock phosphate and the fact that watercress cultivation methods have the potential to result in environmental damage , are clear drivers, as with soil-grown crops, to breed for watercress with improved PUE.