Tag Archives: rolling benches for growing

The U-shaped pattern is explained by the relationship found between urbanization and land value dynamics

As previously discussed, the high degree of correlation between precipitation and maximum temperature means would introduce multicollinearity if both were included in our analyses. In addition to including the mean precipitation values, we test the impact of short-run temperature and precipitation variability on likelihood of sales and land sale value. None of the climate variables studied impact the likelihood of selling farmland in Riverside County from 2000-2017. The 5-; 10-; and 30- year mean precipitation also do not impact farmland value. This is similar to the results in Deschenes and Kolstad . However, short-run precipitation variability has a significant influence on farmland value. A unit increase in the 5-year precipitation coefficient of variation reduces the value of farmland by 56% per acre. Population rate exhibits a significant relationship with both likelihood of land sales and land value. For example, a unit increase in the 5-year population rate decreases the likelihood of selling farmland by 32%, and increases farmland value by 85%. The exact relationship varies across model specifications, but remains significant. Further, population rate exhibits a U-shaped relationship with likelihood of land sales and a hill shaped relationship with land value. Urbanization naturally follows from population increase, and urbanization tends to increase the value of farmland . This may provide incentives to growers to hold on to their land, rather than selling it. However, the marginal productivity of farmland continues to decline with increasing urban encroachment . And, this makes selling farmland more attractive. Citrus and vineyard are less likely to be sold than avocado, while all land uses tend to be more valuable per acre than avocado. The significance of citrus and vineyards tends to vary across model specifications,grow racks with lights although that of general irrigated agriculture and dates remains robust across these specifications.

At the water district level, the results suggest that more valuable farmland is more likely to be sold. Coachella Valley Water District has the most valuable farmland compared to the other 3 districts. This suggests that, controlling for other factors, the characteristics of a given water district may add significant value and may be sold to achieve a positive return rather than minimize a loss.Resilience to water scarcity is fundamentally related to grower responsiveness to the external environment. We have quantified grower responsiveness to farm- and parcel level microclimate in two desert and two coastal counties in Southern California, using primary survey data . Our metrics include gross revenue per acre , likelihood of technology adoption , land value per acre , and likelihood of land sale . Although we study several grower and farm characteristics, climate, water source, farm type, and share of income from agriculture are the most robust variables in our farm-level analyses. The results of the parcel-level analyses of Riverside County in Chapter 6 suggest that short-run variability in annual precipitation may have negatively impacted land value over the past 17 years, though a relationship with precipitation variability and the likelihood of land sale during this same period is not supported by our results. Our analysis of grower responsiveness begins with a farm-level Ricardian model using several micro-level variables collected from our survey instrument . We study the climatic impact on gross revenue per acre in 2014, which is an annual measure of farmland productivity. In Chapter 5, we evaluate the extent to which adoption of irrigation management practices represents adaptation to an increasingly warm and dry climate. These monitoring practices require growers to be more pro-active in scheduling irrigations , and minimizing inefficient leaching practices , and thus represent the next generation of on-farm water management advances. The parcel-level analysis of Riverside County in Chapter 6 includes two complementary analyses: an exploratory analysis of the extent to which likelihood of land sales are impacted by short-run fluctuations in weather; and an analysis of the impact of these short-run fluctuations on land values.

These studies focus on adaptation to extreme climatic events, such as the droughts experienced in Southern California from 2007-2009 and 2011-2016. We introduce two sets of dynamic variables into the analysis: climate and population. Not only do we explore the extent to which these dynamic variables individually impact parcel sales and value, but we explore a preliminary relationship between likelihood of a sale and the relative value of the parcel. In addition to our empirical analyses, we learned how to construct a complex spatial dataset from primary data and existing public data sources on agricultural land values, climate, soil, groundwater, zoning, and utility boundaries. Chapter 3 provides detail on the questionnaire development as well as these multiple external data sources. Ultimately, the benefits of creating a rich dataset outweighed the cost in time.The 5-year total annual precipitation mean and 5-year total annual precipitation variability are both significant in both our binary logistic regression analyses. The positive relationship between the precipitation mean and adoption is counter-intuitive. We would expect this relationship to be negative because a decrease in precipitation associated with the drought would influence growers to monitor water quantity/quality if this grower were using monitoring as an adaption to the drought. We also observe a positive relationship with 5-year total annual precipitation variability, as we expected if monitoring were truly an adaptation to the drought. It is challenging to reconcile these seemingly contradictory results, and ultimately we are cautious about drawing a strong conclusion either way. Precipitation is a complex phenomenon, and further analysis with a larger sample may be necessary. Farm type and percentage of income generated from agriculture may be stronger determinants of adoption. Adoption that is not consciously tied to perceived changes in climate is often called “autonomous adaptation” . This is often observed in the short-run as relatively quick-fixes to production plans.

Given projections of increased frequency and duration of droughts during the current century, growers will develop the most effective, cost-minimizing strategies if they are intentionally addressing these long-run climatic changes today. Almost 1/3 of growers in our sample view drought as their primary threat to water security, and a greater link between monitoring and drought mitigation may even increase the level of adoption in the short-run. In addition to UC Cooperative Extension programs, there are several competitive grants that could incentivize growers to think in these intentional terms. As such, monitoring soil moisture and salinity could be a gateway into managing for long-run climatic changes.Yet, based on the results from our logistic regression, growers who primarily receive their information from state and federal institutions are roughly 3 times more likely to adopt either monitoring practice than those who receive from other sources . This suggests that government programs may benefit from strategic partnerships with industry and small farmers’ networks, without compromising their neutral political role. UCCE and NRCS, in particular, may be able to streamline and leverage their water conservation initiatives with other state government institutions . Our results from the farm-level Ricardian model suggest that a 5% increase in water price increases gross revenue per acre by 1.4%.1 We also study how frequently water price has increased over the past decade. We find that increasing the number of times the price has increased by one unit ,rolling benches for growing increases productivity per acre by 3.4%. This suggests that water price may direct growers to produce higher value crops. Future research on the role of price increases and frequency of these increases for lower value crop farms is important. The challenge is that crops with the lowest value per acre tend to be produced in districts with senior water rights, which do not regularly implement water price increases . Notably, although Coachella Valley Water District holds senior water rights, they have increased agricultural water price 4 times over the past decade. In constructing our dataset, we benefitted greatly from the spatial data from several generous agencies . We also lost both time and data due to poor quality data, which these agencies dedicate valuable resources to collect. Most surprising was the lack of standardization in parcel identification numbers between files from the same agency . There may be a role for academics in setting standards or creating repositories of quality data. The results from the two analyses in Chapter 6 suggest that the relationship between farmland sales and farmland value is attribute specific. Population influences sales and value in the opposite direction, whereas water district and land use attributes influences sales and value in the same direction. Even with limited resources, we were able to collect complete data on 187 growers. This suggests that growers are responsive to providing information to universities. We included a comments page in our survey, which we did not evaluate in our empirical analyses. Many of the comments suggested these individuals were receptive to information that would help them with their production plans , but they did not know how to find or even translate the information. One grower even commented, “We are not your farmers. You are our research university.” There is high potential to foster a positive relationship with growers both directly and, indirectly, through extension research. Perhaps growers could serve as partners in collecting quality data that would prove invaluable to academic research.We did not anticipate the large share of tree crop growers in our sample. This suggests that such growers are both more abundant, and likely more responsive to surveys.

Coupling this with the results from Chapter 6, which reveal that avocado parcels were most devalued and more likely to be sold in Riverside County, warrants a focused analysis on tree crop growers. It also warrants a separate analysis of field crop growers. More data, both across time and space, is needed to evaluate the likelihood of land sale and the potential implications of climate change. As analytics become increasingly accessible, it will be interesting to evaluate the adoption of these data tools and the extent to which productivity is affected. Indoor dust is the most commonly used material to assess microbial exposures in the built environment for studies that link to human health and disease. While the relationship between actual inhalation exposure and microbial measurements from aerosols is more straightforward than for house dust, bioaerosols are highly dynamic in nature and consequently difficult to collect in a way that represents average conditions. House dust is thought to be a long-term integrated sample of particles that have been airborne, thereby proving a composite view of microbes in the indoor environment. Another reason for the popularity of dust samples is the convenience of collection, which typically does not require costly sampling equipment and can be done in a standardized manner even by building occupants themselves and thus enables high replication, all major virtues in large epidemiological studies.There are different types of house dust samples and many ways to collect a sample. Here, we differentiate between dust reservoirs, such as floors and mattresses, and airborne particles that become settled dust. Reservoirs of dust are a popular choice for collecting an integrated sample of what building occupants may be exposed. However, some studies that relate different house dust sample types with bioaerosols sampled through active collection find that sampling reservoirs of dust may not closely represent airborne, inhalation exposure. Reservoir house dust and airborne particulate matter can be disconnected for several reasons. First, there are biases in the settling of small particles, and settled communities are expected to inefficiently contain small-bodied microbes leading to their under representation relative to larger bodied taxa. Second, in the case of floor or mattress samples, the dust also contains material tracked indoors on shoes, paws, or clothes, and in the case of mattress dust, the occupant is the major source of microbial material. Third, the time window sampled by dust reservoirs is variable and typically not precisely known. Instead, studies assessing different indoor sampling approaches attest that a much closer representativeness of actual airborne exposure is dust that settles on a standard sampler surface located above floor level. Passive collection on an elevated surface has two specific advantages: first, particle collection onto the standardized sampler surface occurs over a discrete and known time period. Second, placing passive samplers on a sufficiently elevated surface likely captures airborne dust rather than tracked-in, floor-based particles that may never get sufficiently airborne to contribute to human inhalation exposure. Due to these features of elevated surface samples compared to dust reservoirs, passive collectors of settled dust have been used in several studies, health-based and otherwise, to assess the microbes that occupants encounter in the built environment.

Confirmation procedures included a chest X-ray and an on-the-spot sputum examination

These systems also offer a unique opportunity to tailor crop characteristics to changing consumer preferences by altering environmental conditions such as light quality for example , where blue light has been used to increase the glucosinolate content of several Brassica species including, pak choi and watercress . Here we investigate differences in yield, morphology, and glucosinolate content of watercress grown under three different cultivation systems.This research provides foundation information to suggest that high yield watercress crop production is possible in vertical farming systems and that watercress quality may be further enhanced for improved anti-cancer characteristics. We have shown that the quality and yield of the leafy green salad crop watercress can be significantly improved by growth in an indoor vertical hydroponic system, enriched in blue light. The CDC ranked watercress as the most nutrient dense crop based on the content of 17 nutrients that are associated with reducing chronic disease risk . Our results show the yield and nutrient content of watercress can be enhanced even further by utilizing a novel vertical indoor growing environment other than the current commercial system used in the UK. Yield increases may be explained by the ability to tightly control environmental conditions in the VF that generate a consistent optimal nutrient and temperature environment. The increase in glucosinolate content from UK to CA is probably explained by heat stress in CA,cannabis drying system with the maximum temperature recorded at the CA site at 43.8 ◦C compared to 30.9 ◦C for the UK. Glucosinolate accumulation is associated with improved heat and drought stress tolerance in Arabidopsis and increases in GLSs are observed in heat-stressed Brassica rapa .

Increases observed in GLS content in VF can be explained by prolonged blue light exposure and a longer growth period . The mechanism of different LEDs on GLS biosynthesis regulations still remain unclear, but a short-duration blue light photoperiod increased the total aliphatic GLSs in broccoli . A similar result from a genome wide association mapping of Arabidopsis also revealed that blue light controlled GLS accumulation by altering the PHOT1/PHOT2 blue light receptors . Increasing blue light in the VF increased total GLSs content and although not statistically significant, it confirms the study by Chen et al. that showed increased GLSs content with increased blue light. Rosa et al. showed that GLS concentrations are more sensitive to the effect of temperature than of photoperiod and this is consistent with our results in total GLSs between the UK and CA sites. Our results support the idea that indoor farm cultivation is effective in promoting health-beneficial chemical properties. Watercress produced PBGLS in both the VF treatments, but this compound was not detected in either the UK or CA trials. PBGLS strengthens the nutrient profile of watercress. PEITC derived from PEGLS has already been proven to be an extremely effective naturally-occurring dietary isothiocyanates against cancer . Inhibitory potency increases several-fold when the glucosinolate alkyl chain gets longer , suggesting that PBITC, with its elongated alkyl chain compared to PEITC, may contribute an additional health benefit to this super food, although this remains to be proven. It is evident that watercress is particularly well-suited for indoor hydroponic growing systems, where plants exhibited the highest yielding leafy growth with improved nutritional profiles, ideal for consumer preferences. Altering the blue:red light ratio may further enhance the anti-cancer properties of this highly nutritious salad crop, but further studies are required to hone the light recipe for indoor cultivation. Tuberculosis is a major infectious disease that causes illness and death worldwide . In 2006, there were about 9.2 million new TB cases and 1.7 million TB-related deaths [World Health Organization 2008].

Most new cases and deaths occurred in Asia and Africa. In Nepal, a South Asian country, TB is a major public health problem , with an overall annual incidence of all forms of TB estimated at 176 per 100,000 persons . A range of social, environmental, and behavioral factors influence exposure and susceptibility to Mycobacterium tuberculosis infection. Identifying TB risk factors and minimizing exposure to them could reduce the TB burden in Nepal and other developing countries. Active tobacco smoking, for example, has been shown to be a risk factor for TB, presumably by damaging immune and other protective mechanisms, allowing TB infection to prosper . The composition of tobacco smoke has many similarities to that of indoor cooking smoke from biomass fuel , exposure to which is common in the developing world, including Nepal. Therefore, an association of TB with indoor cooking smoke is plausible. Six previous epidemiologic studies have investigated whether an association exists between TB and exposure to cooking-fuel smoke . Although four of these studies found some evidence of an association, all the studies had limitations. The first study to find an association between exposure to cooking-fuel smoke and TB presented limited data on potential confounding factors, and the risk model was adjusted only for age, which left open the possibility of confounding by socioeconomic factors or smoking . Mishra et al. also reported evidence of an association; however, they used data from the 1992–1993 Indian National Family Survey, which was based on self-reported TB status. This leaves the possibility of outcome mis-classification. A third study found an association between cooking smoke exposure and TB but included no validation of key components of the questionnaire . In a study conducted in Malawi, Crampin et al. found no association between cooking smoke exposure and TB, but the study participants varied little in the type of fuel they used, and the risk model was adjusted only for age, sex, area of residence, and HIV status, leaving open the possibility of confounding by other socioeconomic factors or smoking. The fifth study, conducted in South India by Shetty et al. , also found no association of cooking-fuel smoke with TB, but they did find an association between TB and not having a separate kitchen. The sixth study was conducted by Kolappan and Subramani in Chennai, India; they found a marginal association between biomass fuel and pulmonary TB in their study population [adjusted OR = 1.7; 95% confidence interval , 1.0–2.9]. The study participants in this study were primarily men but because women do most of the cooking, they are more likely to be exposed to smoke from cooking fuel. We conducted a TB case–control study in the Pokhara municipality of Nepal where cooking with biomass fuels in unvented indoor stoves is a common practice.

Our main objectives were to confirm results of earlier studies using clinically confirmed TB cases and to investigate possible confounding of the relationship using a validated questionnaire and exposure assessment in the kitchens of a subset of participants’ houses.old, who visited TB clinics in RTC and MTH and who had been newly diagnosed with active pulmonary TB by chest X-ray and positive active sputum smears , which are routinely conducted at the hospital using methods recommended by the WHO . Women who were pregnant, who were on chemotherapy for cancer, who had HIV/ AIDS or diabetes, or who had a history of TB were excluded from the study. Controls were recruited from outpatient and inpatient departments at the MTH, in the same months when cases were identified. For each case,rolling greenhouse benches the control subjects were the first eligible female patients without pulmonary TB, matched to cases on age , who presented at MTH between 0900 and 1000 hours after case enrollment. Controls were excluded from the study for the same reasons as for the cases. Control subjects were interviewed only after medical screening confirmed that they did not have TB. The ratio of cases to controls was 1:2. After obtaining an informed oral consent to participate, all cases and controls were interviewed face-to-face by trained interviewers shortly after diagnosis while they were still at the hospital. The three interviewers were unavoidably aware of the case or control status of the interviewees but were not aware of the main exposure of interest or hypothesis of the study. All interviewers interviewed both cases and controls. The questionnaire collected data on education level, area of residence , history of use of cooking fuels and stoves that included present and previous cooking fuels and stoves, present kitchen type and location, kitchen ventilation, house type, participant’s smoking history and smoking status of family members, alcohol consumption, vitamin supplement consumption, use of mosquito coils and incense, household crowding, vehicle ownership, and annual income level.Liquefied petroleum gas and biogas were designated “gaseousfuel stoves” , which was used as the reference category for most analyses compared with kerosene-fuel stoves and biomass-fuel stoves . Very few participants reported burning biomass in stoves with flues or chimneys venting to the outside, and no one reported using an electric cooker. For this reason, no separate category was created for vented BFS, and these subjects were included in the BFS category. We examined the extent of agreement of responses on the exposure information obtained during face-to-face interviews at the hospital with data obtained from actual inspection of these features in the houses of the first 28 study participants . The effect of mis-classification was calculated in terms of sensitivity and specificity. We combined information on kitchen location and windows in the kitchen to create a composite dichotomous variable for ventilation. “Fully and partially ventilated kitchens” included open-air kitchens, separate kitchens outside the house, and partitioned kitchens with windows inside the house. This was used as the reference category for ventilation. Unventilated kitchens included partitioned and non-partitioned kitchens without windows inside the house. We were unable to clearly interpret questionnaire data on closing doors in a way that could be used to characterize ventilation. To calculate the number of pack-years of smoking, we combined the information on the average number of tobacco products smoked every day multiplied by the duration of smoking in years divided by 20, assuming that a pack of cigarette contains twenty cigarettes/bidis. One participant who reported she smoked a hukka was excluded from this analysis. We calculated crude odds ratios between exposure and outcome. We decided a priori to include all statistically significant variables in the model, as well as any other recognized risk factors for TB. Then we applied a stepwise backward elimination model, with a variable selection criterion of p = 0.2, to all the variables to identify any others that should be included in the final model. Using the selected covariates, we constructed a multivariate unconditional logistic regression model for risk of TB. We calculated adjusted female population-attributable fractions and associated CIs using the aflogit command in Stata statistical software . This procedure assumes that the proportion of controls exposed is a good estimate of the proportion exposed in the target population.Four potential interviewees did not meet the inclusion criteria: two were diabetic and two were HIV positive. During recruitment, one potential control was found to have pulmonary TB and was transferred to the case group. Except for one control, all potential interviewees agreed to participate in this study. In total, we recruited and interviewed 125 cases and 250 controls. Cases were more likely to be referred by a health care professional than were controls . This might reasonably be expected because TB causes serious illness, but many of the controls would have had much less severe conditions. Table 1 lists descriptive data for the cases and controls, with unadjusted ORs and CIs. With the exception of the income variable, few data were missing. Confirming the success of the matching process, distributions of cases and controls were similar in terms of age. Most cases and controls were from the Kaski district. Cases were more likely than controls to be Buddhist, to live in urban and periurban areas, to reside in poorer quality houses , to be illiterate, to have non-partitioned and unventilated kitchens indoors, and to use kerosene wick lamps as their main source of light. Cases were also more likely than controls to regularly consume alcohol, to be tobacco smokers, to have more smokers in the family than controls, and to have not always lived in their present house. We think that, to some extent, the latter variable probably captures the likelihood of previously having used other cooking fuels.