Consumers and stores could return infected eggs for a full refund

Infected eggs from these two major egg producers were distributed in fourteen U.S. states, including California. Eggs were recalled using specific plant numbers and codes that allowed tracing back to the box level, leaving no infected eggs in stores.The three egg recalls received extensive national and local media coverage on the television, radio, newspapers, and the Internet. To measure media coverage of the event, we conducted a Lexis-Nexis search, which gave us the daily count of newspaper articles that appeared on the 2010 Salmonella egg outbreak, starting 15 days before the event up to 60 days after the event. Figure 1 shows the number of articles in major newspapers that include the words “Salmonella” and “Eggs” on a given day. Media interest persisted over a six-week period following the event, in particular covering farm inspections that found numerous violations and showed that the egg farms were infested with flies, maggots, rodents and overflowing manure pits, as well as both farm owners testifying before Congress. The fact that there were three consecutive egg recalls within one week could have led consumers to think that this was a major outbreak, and not a regular food recall. Furthermore, given the information provided by the media coverage, some consumers may have obtained information or updated their beliefs on the egg industry as a whole. If consumers were perfectly informed, did not update their beliefs, and expected no further recalls, we could anticipate no effect of the event on consumer purchases. However, if consumers did not have perfect information on the outbreak or the recall codes,macetas de 10 litros updated their beliefs about the egg industry, or “overreacted” to the recalls, we could expect a drop in egg purchases following the event, at least temporarily.

We find that the latter was true.Using a unique product-level scanner data set of a national grocery chain that has stores in both high and low income zip codes, we examine how consumers reacted to the three consecutive egg recalls. First, we test whether consumers changed their egg purchases in California following the recalls. We examine media coverage on the highly publicized outbreak and hypothesize that media coverage is the channel through which consumers became informed about the event. Second, we study whether consumers substitute away from conventional eggs towards other types of specialty “greener” eggs that may be perceived as having a lower probability of Salmonella, such as organic or cage-free eggs. Eggs are currently produced under a variety of methods, but 95% of the national egg production in 2010 came from conventional battery cages. In our California and Washington sample, around 90% of eggs sold came from battery cages. Table 1 summarizes some of the differences between conventional eggs and non-conventional eggs. It is unclear if consumers were aware of the debate in the United States about the link between the type of egg and the probabilities of Salmonella infection. We hypothesize two possible results for purchases of unaffected eggs. On one hand, consumers might substitute away from conventional types of eggs to non-conventional specialty eggs . On the other hand, some consumers might choose to reduce all egg purchases, leading to a decline in purchases of all types of eggs. Third, we investigate whether different socio-economic groups reacted differently to the egg recalls. In particular, we look at whether income and household size affect the response to the recalls. To do this, we use demographic data for the zip code where the store is located. Income may affect the response if wealthier consumers are able to substitute to greener alternatives, which can cost up to twice as much as traditional shell eggs.

Finally, we examine whether separate areas within California reacted differently to the egg recalls. Due to its distribution system, our national grocery chain had infected eggs only in Northern California. We use variation within California to test whether consumers in Southern California reduced egg purchases as well. We use a technique known as differences-in-differences to estimate the effect of the three recalls on egg sales and use a control state that did not receive infected eggs, Washington. We are also able to control for seasonality by using data from previous years around the event date. The differences-in-differences approach consists in comparing changes in egg purchases in affected areas in California to changes of egg purchases in comparable but recall unaffected areas in Washington. If we were to focus only on the changes in California, we could not conclude that those changes were caused by the recalls. We could only show that they are correlated with the recalls. Indeed, other confounding factors, such as macroeconomic conditions, could be responsible for changes in California egg purchases. We net out such factors by using changes for comparable stores in Washington as counter factuals. We use the fact that infected eggs could be traced to the box level to establish a clear definition of the treatment and follow a panel of over 600 stores during a four-year period. Further, given the geographical distribution of infected eggs, we are able to measure potential spillovers to unaffected areas of California.We begin by plotting the evolution of daily sales around the “event week” in California. Figure 2 plots changes in egg purchases for all shell eggs for stores in California only. The category all shell eggs includes 2 classes and 7 sub-classes . The figure plots data starting 30 days before the “event day” up to 35 days after the event day. Changes in egg purchases take into account price, as well as factors that are constant across stores, aggregation levels and day of the week .

Egg sales show a large drop a few days after the first recall and a small increase between the second egg recall and the third recall. Sales reach their lowest level in the time period around 11 days after the first egg recall. This suggests that, if egg purchases decreased due to the egg recalls, there was a small time lag between the time the recalls were made and the time that the effect was reflected in lower purchases in stores. Using our econometric model, we proceed to formally test the effect of the three egg recalls and find a 9% significant reduction in egg sales in California. Given an overall price elasticity for eggs in U.S. households of around -0.1, this sales reduction is comparable to an almost 100% increase in price. Consistent with a rather inelastic demand, the effect is very similar with and without prices. We find that the decrease in sales was driven by a drop in purchases of traditional large shell eggs and find no evidence of substitution toward other greener type of eggs, such as organic or cage-free eggs. More specifically, we find that purchases of large traditional shell eggs significantly decreased by 10% in California in the month following the event. Large traditional eggs had the largest market share of sales in our sample in 2009 . Sales of the other types of eggs do not change significantly due to the recalls. For jumbo, brown, cage-free and nutrient-enhanced eggs , we find no significant effects of the recalls. Sales for extra-large traditional shell eggs and for organic eggs seem higher but the recalls still have no significant effect.When matching each grocery store with the socio-economic characteristics of the zip code in which it is located, we are able to investigate heterogeneous effects of the recall. We study whether income and household size affect the response to the recalls,macetas de 7 litros where income is the demeaned average income in the zip code in which the store is located and household size is the demeaned average household size in the zip code in which the store is located. Socio-economic data come from the 2000 U.S. Census. While we find no correlation with income, we do find that areas that had a larger than average household size decreased egg purchases significantly more. A caveat to the results is that it is possible that more affluent customers diverted egg purchases to farmers’ markets or high-end grocery stores after the egg recalls and thus the estimates would suffer from selection bias. The data allow only for the identification of effects with purchases undertaken at the national grocery chain. We also find differentiated effects among Northern and Southern Californian stores. Although the national grocery chain had infected eggs only in Northern California, we find that Southern Californian stores had lower egg sales as well. The overall sales reduction in Southern California was half as large as the reduction in Northern California, and is consistent with media and reputation effects being significant determinants of demand, even in the absence of an actual food recall. Studies on the effects of safety warnings on spinach , beef or fish have also found significant consumer responses. However, the persistence of the effect may vary depending on the type of good and availability of substitutes. For example, while the effect of a safety warning on spinach had a long-term effect, our results for eggs suggest that the effect was temporary.

To test the robustness of our findings, we perform several checks. First, we test the sensitivity of the baseline results to various assumptions about the seasonality parameters. We use only data for one year before the recall instead of using, as above, all previous years . This yields very similar drops in purchases as when we include all previous years. Second, we test the sensitivity of the baseline results to using Washington as a control state by excluding data from Washington and using stores in Southern California as controls. The rationale is that we may assume that stores in Southern California have similar trends to stores in Northern California. Once again, using Southern California stores as counterfactuals for Northern California store patterns yields very similar estimates of the egg recalls. Third, we test the sensitivity of the baseline results to using only one month after the event week. We obtain data on a second post-event month and include a total of eight weeks after the event week for all years. While this additional robustness check gives us similar results to the ones from the main specification, we find that the effect lasted more than one month.When matching each grocery store with the socio-economic characteristics of the zip code in which it is located, we are able to investigate heterogeneous effects of the recall. We study whether income and household size affect the response to the recalls, where income is the demeaned average income in the zip code in which the store is located and household size is the demeaned average household size in the zip code in which the store is located. Socio-economic data come from the 2000 U.S. Census. While we find no correlation with income, we do find that areas that had a larger than average household size decreased egg purchases significantly more. A caveat to the results is that it is possible that more affluent customers diverted egg purchases to farmers’ markets or high-end grocery stores after the egg recalls and thus the estimates would suffer from selection bias. The data allow only for the identification of effects with purchases undertaken at the national grocery chain. We also find differentiated effects among Northern and Southern Californian stores. Although the national grocery chain had infected eggs only in Northern California, we find that Southern Californian stores had lower egg sales as well. The overall sales reduction in Southern California was half as large as the reduction in Northern California, and is consistent with media and reputation effects being significant determinants of demand, even in the absence of an actual food recall. Studies on the effects of safety warnings on spinach , beef or fish have also found significant consumer responses. However, the persistence of the effect may vary depending on the type of good and availability of substitutes. For example, while the effect of a safety warning on spinach had a long-term effect, our results for eggs suggest that the effect was temporary.

The Qavail conceptualizes the maximum limit to water supply from the soil-root-stem system

The understanding of processes affecting plant water availability has fundamental and applied implications. Recent studies have recognized the key role of roots in promoting acclimation to different types of stress; mainly through preferential growth and control of hydraulic properties that regulate transpiration . A better understanding of root response is, therefore, key for understanding water fluxes through the soil-plant-atmosphere continuum. Accordingly, here we examine the effect of root growth and plant hydraulic conductance on water availability for canopy transpiration of young walnut trees under different levels of water stress.The study was conducted from April 2015 to July 2015, using nine 8-month-old potted walnut trees cv. Chandler, grafted onto Paradox root stock in an experimental greenhouse at the University of California, Davis. Plants were grown in 0.02 m3 pots filled with a 1:3 mixture of a fine sand and organic compost. As the experiment was conducted over a short period and the plants were young, the size of the pots was considered suitable. Pots were kept covered with aluminum foil to avoid soil evaporation and their transparent walls were covered with plastic sheets that were black inside and white outside, to protect roots from light exposure. All pots were maintained at field capacity for at least a week before the beginning of each 10-days period experiment. Replicates were monitored over time due to the careful tracking of soil-plant properties and limited availability of leaf psychrometers and high precision weighing scales for all individuals. Hence,macetas 30l the experiment was replicated using three different plants per treatment monitored over 10- days in three different time periods , for a total of nine receiving one of the irrigation treatments and three control plants.

While temporal replications integrate the effect of different insolation and temperature conditions in the greenhouse at each 10-day sampling event, we expect to observe consistent shifts between T100, T75, T50 throughout the experiment.Stem water potential was measured on expanded terminal leaflets located close to the trunk, every 15 min and averaged to hourly values, with a psychrometer/hygrometer , model PSY-1 . The leaflet equipped with the psychrometer was fully covered with an insulation capsule limiting temperature fluctuations . As the monitored leaf did not transpire, the measurement was representative of stem rather than leaf water potential. An independent measurement of stem water potential was carried out weekly on fully expanded leaflets with a pressure chamber . Prior to this destructive measurement, leaflets were enclosed in foil-laminate bags for at least 10 min . Plant transpiration rate was quantified by automatic weighing of pots on a high precision weighing scale every ten minutes, averaged to hourly values. Draining water was collected daily in plastic reservoirs attached laterally to the bottom of the pots by flexible rubber tubing. Hence, the weight of leaching water did not affect the weighing scale reading until its collection. Both the added irrigation water and collected leachate were weighed and removed from the water balance in order to evaluate the weight loss due to TR . Bulk soil water potential at soil-root interface was monitored by one tensiometer per pot, placed at approximately the midpoint of the root system at 0.2 m depth, and recording data every ten minutes to generate average hourly values. Its porous ceramic cup was connected through a water-filled PVC tube and a smaller acrylic glass tube equipped with a pressure transducer. A rubber cap on top of the tensiometer ensured its air tightness.

All plant and soil measurements were continuously recorded with a data logger located inside the greenhouse. Hourly average air temperature and relative humidity were obtained in an automatic micrometeorological station placed inside the greenhouse. The reference evapotranspiration was obtained by use of an atmometer Model E , that gives one pulse at each 0.254 mm of evaporated water . Hourly vapor pressure  deficit was estimated by the difference between saturated and actual vapor pressure. Saturated vapor pressure was calculated using air temperature based on the Tetens formula . Actual vapor pressure was obtained by saturated vapor pressure multiplied by fractional humidity. We used an empirical water stress indicator based on plant relative transpiration . For each plant, the potential daily transpiration was estimated as a product of the plant standard daily transpiration by the ratio of the actual daily transpiration to TD* of the unstressed plant . The water stress indicator was simply calculated as the ratio of TD to plant potential daily transpiration. An undisturbed leaf was harvested and water extracted using a custom-made cryogenic distillation system suitable for isotopic analysis, adapted from previous studies of this kind . Briefly, the leaves were transferred to individually cut 1.27 cm diameter pyrex tubes where the leaf material was held in place by stainless steel wool. After attachment to a vacuum manifold, leaves were frozen in liquid nitrogen and air evacuated to 100 mTorr. The tube was then flame sealed to preserve the vacuum, and subjected to gravity assisted cryogenic distillation, the top of the tube at 110° C, bottom at −20° C. After distillation, the tube was removed and ice water isolated by flame sealing the tube again to separate water and leaf material. Leaf material was separated and ground to a powder using liquid nitrogen in a mortar and pestle. 3 mg samples were submitted for δ13C determination at the UC Davis Stable Isotope Facility by continuous flow GC-IRMS on a PDZ Europa ANCA-GSL elemental analyzer interfaced to a PDZ Europa 20- 20 isotope ratio mass spectrometer . The water samples were transferred to 2 mL vials and was analyzed for δD by equilibration with water vapor and added hydrogen gas, assisted by a platinum black powder catalyst. Next, CO2 was added to the system and equilibrated with water vapor for δ18O analysis.

Water analysis was performed at the University of Miami by using multi-flow system connected to an Isoprime mass spectrometer . To standardize isotopic data, values are reported in del notation with reference standards as in the equation below. The visible root length was monitored weekly over five weeks from the beginning of each 10-days period experiment by combining root mapping on the transparent walls of the pots and observation of inner root length with minirhizotrons , which provide a nondestructive method for repeated root observations . In addition, weekly root length observations started five weeks before each 10-days period experiment in order to follow the Rl pattern through time. Minirhizotrons consisted of transparent acrylic tubes with an inner diameter of 50 mm, and wall thickness of 3 mm. We used one tube per pot, installed at an angle of 45°, and sealed with silicon. Analyses of Rl were performed weekly with a BTC minirhizotron digital image capture system , located inside the minirhizotron tube. Each observation consisted of systematically taking pictures at one-centimeter intervals from the top to the bottom of the pot in three dimensions, totaling approximately 90 pictures per tube. The Rootfly software was used to analyze root length semi-automatically.Analysis of covariance of linear regressions between hydrogen and oxygen isotope ratios of leaf water showed significant differences in intercept between treatments , but no differences in slope . All experimental pots were covered to suppress soil evaporation, therefore, differences between treatment regression lines relative to the source water line are attributed to changes in leaf transpiration. Differences in intercept tracked expected declines in transpiration rates under drought stress and are consistent with changes in iWUE inferred from carbon isotope ratios . There was no difference between T100 and T75 with respect to iWUE or d-excess, indicating physiological acclimation and maintenance of a steady balance between photosynthesis and transpiration. However, iWUE and dexcess of T50 trees was significantly different from the others, indicating low stomatal conductance .Snapshots of root growth over time are shown in Fig. 6. In general, under well-watered conditions, new roots started to grow before the old roots died and were more frequently observed . Large variability was recorded for relative external and internal patterns of root growth at each sampling event. However, the cumulative total and living root growth detected by the minirhizotron showed significant changes with greater growth observed in the well-watered treatment . Crucially,maceta 25 litros root growth patterns were proportionally and positively related with d-excess . This indicates the existence of a fundamental trade off between root growth and iWUE , by which canopy transpiration and root development can be estimated based on changes in leaf stable isotope ratios. It is important to note, however, that differences between T100 and T75 with respect to either root growth or iWUE were not statistically significant. Therefore, acclimation is possible at that level and high physiological stress seems to be required to study costs and benefits of such a trade off with respect to changes in water supply.Our observations confirmed the decreasing TR as a response of midday depressions of leaf water potential , showing the minimum ψstem in T50 between −1.0 MPa and −2.0 MPa, which was strongly and positively correlated with ψsoil, explaining low TR under deficit irrigation . Indeed, stomata are expected to be completely closed in walnut trees when leaf water potential reaches −1.6 MPa and similar ψstem values and associated stomatal closure have been previously reported in stressed walnut trees , as transpiration rates decrease to prevent leaf dehydration under moderate to high Tair and VPD .

Otherwise, the strong and positive correlation between TR and evaporative demand was noticed for well-watered plants , as observed in previous studies , followed by strong and moderate water limitation . Multiple lines of isotopic evidence integrate the effect of physiological responses to treatments during the entire experiment and corroborate a significant decline in TR under deficit irrigation. Leaf water regressions show significant deviation from source water with reducing water loss by transpiration earlier under water stress has also been recognized in peanut and pearl millet . Here, our results showed an early and rapid decline in transpiration followed by stabilization of water loss in stressed trees, which is consistent with the fraction of “transpirable” soil water general mechanism of declining TR and with the classic descriptions of the plant water stress function . The nonlinear decrease of TR as a function of ψsoil and ψstem can be seen as a water conservative strategy to prevent water loss and leaf dehydration long before being limited by water supply from the soil-root system . Such a strategy lowers the risk of hydraulic failure and increases the iWUE. Considering that the major part of the walnut orchards are located in areas periodically affected by drought and due to its high water requirement over seasons, this observed trend and its further understanding has a key role in the identification and use of relevant physiological traits in plant breeding programs, allowing greater water-use efficiency under deficit conditions. The observed values of Kh fall in the typical range reported for young tree species and annual crops . Our results highlight the decrease of Kh under moderate and strong water limitation . Water  deficit is one of the most important factors affecting Kh , and its decline in response to decreasing stem water potential under water deficit has been reported in walnut at ψstem approaching −1.8 MPa due to cavitation . However, we observed reduced Kh long before reaching such negative stem water potentials . As our Kh only includes hydraulic resistances between the stem and the soil-root interface, its reduction might have been fostered by a combination of poor soil-root contact under lower soil water content and altered root permeability that were described in other species.It turns out that in the T75 treatment, a reduction of stomatal opening due to water limitation occurred long before transpiration was limited by Qavail. Functionally, such stomatal regulation might play the role of extra security margin against hydraulic failure and translate into a so-called water saving behavior at longer term . The results also suggest that the supply-demand view in plant transpiration modeling is inappropriate for walnut, so that more complex models are needed . Despite the significant effect of water deficit on various plant properties, root growth responses over time did not correlate with any other recorded variable, and could did thus not explain changes of Kh. However, our observations suggest that healthy roots rapidly shifted to decaying roots with the continuity of water stress, which means a reduction of root activity and less capacity to take up water .

Regulations may also limit the ability of specialty crop operations to store water

Microirrigation allows for precise delivery of water to the container-plant system and provides the potential to implement fertigation if controlled release fertilizers are not used or are depleted before the end of the growing season.Freshwater is a finite resource. Yet, demand for water has increased due to population growth and increasing water use by agricultural systems needed to support larger populations . Although most nursery and greenhouse crops do not feed people directly, these plants can enhance human well-being and expand our connection to the natural environment . Globally, agriculture is estimated to use 69% of freshwater supplies, while industry and energy use is 23% and household consumption is 8% . Concerns regarding water scarcity, particularly in arid or semi-arid regions such as the western USA and Australia, intensify during times of drought, but long-term water use continues to be a major problem. The majority of the specialty crops, grains, fruits, vegetables, and nuts consumed within USA and exported around the world are produced in the western USA . During times of drought, allocation and conservation of a limited water supply among agriculture, industry, and household use receive increased attention. During 2015–2016, much of California was in either extreme or exceptional drought,cultivar arandanos the two highest categories, impacting over 36 million people in the state . Growers were forced to fallow land and remove established agricultural specialty crops because of limited water availability. Changing weather patterns can significantly impact both crop yield in non-irrigated land and the volume of water required to supplement rainfall in irrigated lands .

Agricultural systems, in general, will likely need to produce more plants with less water, use lower-quality water, or both . Crop water use efficiency, defined as the water volume required to produce a given dry mass of yield, and water use reduction can be accomplished in part by breeding for drought tolerance , but growers must also conserve water through irrigation and other management practices . Increased crop water use efficiency can be achieved via precise water quantity delivery to the container based on crop-based demand to limit leaching from over-irrigation. Additionally, irrigation type , timing , and use of new technology have been reported to increase irrigation efficiency. Regardless of method, improved water application and scheduling precision reduces the presence of agrichemicals and other contaminants in production runoff .Transport of contaminants from irrigation runoff into the neighboring ecosystem is a concern for all agricultural production, but particularly in specialty crop production . Contaminants of concern in specialty crop operations can either be removed, recycled on-site, volatilized, or transported off-site, depending upon production practices at the operation and prevailing environmental conditions. Contaminant presence, along with increased economic and regulatory pressure to develop alternative irrigation water sources, results in a challenge for many growers. Recycling runoff water for irrigation is an ideal solution from a water quantity standpoint, in that the water is already available on-site, reducing volume of water needed from other sources. This recycled water also contains contaminants that could be detrimental to the environment; recycling water would help to limit agrichemical escape into the environment . Growers are typically concerned about negative impacts of bioactive concentrations of pesticides or phytopathogens which may diminish crop health if they are present in recycled runoff water.

Perception of risk associated with these contaminants represents a significant barrier to grower adoption and use of this readily available water source . Fertilizers deliver plant essential mineral nutrients to ensure optimal growth, but application of fertilizers in excess of plant requirements can result in nutrient leaching; of particular environmental concern are nitrogen and phosphorus . Fertilizer runoff from agriculture, including specialty crop production, is a major problem in a number of impaired waterways and can lead to environmental problems such as algal blooms . The ability to recycle mineral nutrients is perceived as a benefit for some growers, and these recycled fertilizer salts are sometimes accounted for in their nutrition programs, particularly in greenhouse production . Agrichemical residues in water can be detrimental if not mitigated, as both surface water and groundwater can become contaminated . The fate and transport of agrichemicals depends on a number of factors, including location applied, soil characteristics, slope, and timing of rain/irrigation events . Chemicals vary in their modes of action and half-lives in the environment ; thus, managing agrichemical contaminants in recycled runoff can be challenging. However, prevention of contamination and remediation of contaminants to minimize reapplication injury to the crop and environmental/biotic damage is feasible using best management practices . Phytopathogen contamination can create economic and ecosystem stressors, causing disease within both the operation and the surrounding ecosystem via runoff . Economic analysis of production losses attributed to phytopathogens in container-grown specialty crops is not widely available, making it difficult to calculate the impact on grower profits and the surrounding environment. Specialty crop production losses to pathogen infection have been estimated to range from 5 to 30% for some crop taxa, but losses are likely to be crop specific and fluctuate annually based on environmental and production conditions.

Ecosystems may be negatively impacted by the discharge of pathogens from crop production facilities via plant transport from nurseries and eventual pathogen escape into the environment as illustrated by the pathogen causing sudden oak death, Phytophthora ramorum . While fungicide applications can suppress pathogen growth, in general they are not curative. As a result, many growers prefer to minimize potential for crop infection by either sanitizing water before it is used or not reusing runoff. Management of pump intake depth and location within a reservoir were identified by Ghimire et al. as key mechanisms for limiting introduction of pathogen propagules via irrigation water. Additional insights into propagule movement,survival, persistence, and/or pathogenicity in production runoff and their economic and environmental impacts are potential areas of future study In 1972, the USA passed the Clean Water Act, which created an impaired waters list [also known as the 303 list], which identifies bodies of water that do not meet water quality standards, including chemical contaminants, dissolved oxygen, excess algal growth, or other factors that may reduce the ecological health of a waterway . The goal of this list is to remediate impaired waters and remove them from this list. Many areas of the USA contain impaired waterways. In 2016, the US Environmental Protection Agency listed 42,509 impaired waterways on the 303 list due to aforementioned impairment. Cumulatively since 1995, 69,486 TMDLs have been assigned to water bodies, of which 13,313 are for high pathogen loads, 6235 for excessive nutrient loads, 3950 for excessive sediment loads, and 1351 for pesticides . Although agriculture is not the sole contributor to impairment in these impaired waterways, reducing the environmental impact of agriculture via non-point source contaminant reduction should be a conservation goal.Runoff from specialty crop container operations is from two sources: uncontaminated water and operational water. In this context, uncontaminated water is water from rainfall events that has not come into contact with production areas, crops, agrichemicals, retention basins, or runoff collection reservoirs that collect and retain production runoff, nor should it contain contaminants above background levels . Runoff from a greenhouse roof is an example, as this water should not require treatment prior to leaving an operation or mixing with operational water to supplement the irrigation water supply. Operational water is any water flowing from, in, through, or around production areas. As a result of contact with soils, agrichemicals, and phytopathogens, this water may have elevated concentrations of contaminants, which may require treatment before reuse or release, depending on operational needs and local regulations.Ideally, both operational water and uncontaminated water would be captured, treated, and released from or reused by container operations. This is not always possible for nursery or greenhouse operations for a number of reasons. Often, operations have geographic limitations that constrain their capacity to capture runoff. Rainfall events in some regions of the USA are intense over short durations, resulting in runoff volumes that exceed the capacity of existing containment infrastructure. In some parts of the country, a high water table can limit feasibility to capture or treat runoff water. Saltwater intrusion and storm surges are also major concerns, particularly in coastal areas . Some operations, especially smaller or more urban operations, may be land limited, so there may not be sufficient land area to store water for treatment or reuse. Other areas may not be able to store water due to topography or soils . These limitations must be considered when developing regulations and implementing BMPs for a particular area or operation.As populations increase,macetas plastico particularly in the western USA where water is more limited, state and local regulations may limit the amount of water that can be captured or stored at an operation. For example, Oregon requires all users, including nursery and greenhouse operations, to obtain water rights permits to store rainfall in a containment reservoir since it is considered a state resource .

Similar regulations may become more common across the country as water becomes more limited and may be a short-term advantage to producers not under those restrictions.The following information about layout and site design is meant to represent the ideal production scenario; however, site constraints and owner priorities will dictate what is possible. A new operation should be designed to balance water collection, water storage, and production to ensure ample amounts of quality water. Containment reservoirs should be situated at the lowest part of the nursery,allowing water to flow freely towards the containment reservoir while minimizing contact with production areas . Chen reported remediation benefits associated with a multi-reservoir design, where water flows through multiple reservoirs before it is recycled. Pathogens are relatively short-lived without a host; therefore, if multiple ponds are used to increase water retention time, fewer pathogens survive to reinfest plants . If multiple reservoirs are not available, locating the irrigation pump intake as far from the entrance of operational water as possible in order to increase hydraulic retention time and 1 m above the bottom of the reservoir can help reduce pathogen loads applied to crops . In greenhouse operations, one or more cisterns may be used to store irrigation runoff , particularly for ebb and flood systems. Return water must be treated prior to storage or reuse to reduce or remove pathogens, particulates, and other potentially harmful constituents that can impact the irrigation system and plants. One of the most important steps to ensuring efficient capture of runoff water is proper grading and utilization of well-drained bed base such as coarse gravel. These measures can reduce disease incidence by minimizing standing water under containers and convey water to containment reservoirs for reuse or remediation . Grading may be minor or extensive, depending on the layout of the property and the site design. More detailed information regarding infrastructure and surface water recycling is available in Bilderback et al. ; Merhaut ; Yeager .Remediation can be defined as the process of removing chemicals, pathogens, and other constituents of concern to reduce loads of harmful substances to a water system . Contaminant type, required load reduction, and the economics and efficacy of treatment technologies depend on a number of factors at each operation. Below, we highlight research that evaluates various treatment technologies and assess where technologies may be of most effective use in production systems. A summary of each technology, scalability, relative cost , contaminants managed, and relative efficacy for each technology are presented in Table 1.Filtration is accomplished via several mechanisms including adhesion , flocculation , impaction , interception , and straining . Contaminant removal efficacy is in part determined by particle size, contaminant loading rate, and flow rate; these should be considered when selecting treatment technologies. Important considerations for filtration include both the flow rate and the loading rates of contaminants that must be removed, as well as the cost of installation and upkeep .Rapid sand and glass filters consist of tanks that hold sand or glass of a specific particle size . As water moves through the sand or glass, particulates are removed. These filters are able to process large volumes of water quickly . As sand or glass particle size decreases , filters are able to remove smaller particles, but require more force to move the same volume of water per unit time.

Ethylene production by the olive inflorescence was lowest four days before FB

High GA-like concentrations in midsummer reduce generative bud development, and the highest GA-like substance in fruits occurred in June and July . These collective results suggest that gibberellins in developing seeds of fruits on one year old growth suppress development of fruit buds on the apical current year’s shoot growth, resulting in alternate bearing. Thus, alternate bearing is due to inhibition of floral induction , and floral induction in the current year is inhibited by fruit load from the previous year. There is a negative relationship between the current year’s flowering intensity and the previous year’s production . In ‘Manzanilla de Sevilla’ cultivar, 58% of the variance in the number of flowers was explained by production in the previous year. The current year’s yield depends on flowering intensity, which depends on the previous year’s production. This relationship was also found in pistachio. The yield of the previous-year harvest is most strongly and negatively correlated with the yield of current year . However, the specific mechanism of suppressing floral bud induction and development is unknown. The role of ethylene in precipitating plant organ abscission, including floral organs, is clearly defined .It increased to a maximum seven days after FB and this peak coincided with massive flower shedding . Inhibition of ethylene results in longer-lived carnation flowers . In the ethylene biosynthesis pathway, methionine is catalyzed to SAM by SAM synthetase, SAM is then converted to 1-aminocyclopropane-1-carboxylic acid by ACC synthase,macetas cuadradas and ACC is further converted to ethylene by ACC oxidase . The ACC synthase is the targeted compound in limiting ethylene synthesis in tomatoes .

The compound aminoethoxyvinylglycine competitively inhibits ACC synthase activity by binding to the substrate’s active site, preventing ethylene synthesis . AVG is now used on multiple fruit crops. AVG applications to apple trees during harvest slowed ripening, effectively extending the harvest period . AVG inhibited ethylene biosynthesis, increasing peach fruit quality . Similarly, AVG decreased ethylene generation and increased fruit firmness in plums post harvest . AVG treatment delayed cocoa flower abscission and decrease ethylene generation in pear flowers, increasing fruit set and yield . Similar results were found in apples . Whole-tree applications of AVG on ‘Regina’ and ‘Kordia’ cherry trees significantly improved fruit set and yield . AVG application in walnuts increased yield because the high ethylene concentrations in female flowers caused of pistillate flower abortion . The effect of AVG on ethylene suppression has been confirmed multiple times. For example, AVG prevented ethylene generation in rapeseed and sunflower plants . AVG applications inhibited fruit ethylene production in ‘Golden Supreme’ apples . The primary role of AVG is inhibition of ethylene biosynthesis . Extensive research of AVG applications in walnut demonstrated that ReTain™ applied to pistillate flowers successfully decreased ethylene production and resulted in reduced flower abortion . Subsequent orchard trials confirmed these findings. The AVG treated walnut trees produced higher yields than control trees because the AVG reduced pistillate flower abortion, improving fruit set . We hypothesized the short longevity of olive pistils is the primary reason for the low fruit set and yield in olives. We further hypothesized that AVG applications, as ReTain™, during bloom can potentially decrease ethylene generation by olive inflorescences, extend the pistil and ovule longevity for a longer effective pollination period, and increase yield.

Therefore, we tested the ability of AVG, as ReTain™, applied at 25 to 50% bloom to decrease ethylene production by olive flowers, extend the pistil viability, EPP, and potential successful fertilization, and increase fruit set and oil yield in Arbequina olives. The experimental site was a 12 year-old Oleae europeae cv. ‘Arbequina’ orchard located at 38.07°N, -121.21°W, farmed commercially by Lodi Farming Inc. The orchard comprises 59 rows oriented on a north-south axis with ~ 220 trees in each row. Trees are spaced at 5 feet inrow x 13 feet between rows, for 670 trees per acre. We designated this orchard as Orchard A. A randomized complete block design was used in the experiment, with six, eight-row blocks containing two, three-row sets within a block, separated by two buffer rows. The ReTain™ treatments were applied once in every block to three contiguous rows . The center row of the three contiguous rows was used to collect samples and yield data.In 2019, after spraying on May 13th, 2019 , sampling of ethylene evolution started and was repeated daily for 13 days, until there was no difference in ethylene generation between control and treatment trees. It rained on 10 of the 13 sampling dates. From each treatment in each block, two trees, each from the north and south ends of the row, were selected for ethylene measurements. From each tree, two uniform shoots, similar in floral load, facing two directions , and at equal position in the canopy were collected daily for 13 days. They were placed on ice and transported to the lab immediately. In the lab, ~ 0.6 g, or three to five inflorescences were cut from each shoot, weighed on a Mettler balance and placed in a 15 cm airtight test tube. The tubes were placed in a controlled temperature room at 20°C to equilibrate for 1 hour. After equilibration, 10 mL of air was withdrawn from each sealed tube with a 10 mL syringe and injected into Series 400, AGCCarle Gas chromatograph for ethylene measurement. Ethylene production was expressed as µL/.In 2019, olive inflorescence samples were collected and preserved in FAA solutions .

They were further dyed with Aniline Blue and observed using a fluorescence microscope. Pictures of olive ovaries were taken, and pollen tube widths were measured using ImageJ. The pollen tube width was used as a measure of pollen tube growth, which reflected the effect of ReTain™. The treated and control rows were individually harvested on November 15th, 2019, by a Vinestar canopy contact parallel bow rod harvester with a single detached fruit bin traveling at a ground speed of 1.5 mph. The weight of the detached fruit bin was determined before harvest. The fruit weight per row was then determined using a digital in-ground scale with the bin tare entered. After weighing, a 5 kg sample was collected and put on ice for transport to the UC Olive Center Laboratory of Dr. Selina Wang at UC Davis for oil quality analyses.The same experiment was not repeated in 2020 due to strong alternate bearing and a lack of flowers. However, a grower trial was performed; selected rows in two orchards were sprayed on with the same ReTain™ treatment and control, and ethylene emission was measured from inflorescences collected from the sprayed and unsprayed rows. The sprayed and control rows in Orchard B and C were harvested and yields compared on November 15th, 2020, in both orchards. The yield from Orchard A of the 2019 experiment was measured for comparison with the yield of 2019. In 2019, the six treated rows in Orchard A produced an average yield of 3320 lb, with a standard deviation of 408, while the 6 control rows produced an average of 2970 lb, with a standard deviation of 98. With a p-value of 0.067, the difference in yield between ReTain™ treatment and control rows was not significant when the alpha level equaled 0.05. However, it was significant when the alpha level equaled to 0.1 . In 2020, the six treated rows in Orchard A produced an average yield of 1160 lb, with a standard deviation of 290,maceta cuadrada plastico while the six control rows had an average of 1185 lb, with a standard deviation of 369. The p-value was 0.9, showing no significant difference in yield between ReTain™-sprayed and unsprayed rows . The yields across the orchards in 2019 and 2020 were also determined . In 2019, the significant difference in ethylene generation between treated and control trees suggested that ReTain™ worked as assumed: it decreased ethylene generation. Day 0 was denoted as the ReTain™ application date. The confidence bands for ethylene generation were very narrow before day 3 and after day 12 . During those days, some ethylene measurements appeared to be zero and were omitted, because it is impossible to have zero ethylene generation . Fewer ethylene measurements before day 3 and after day 12 resulted in narrow confidence bands. The primary finding was not affected: from day 3 to day 12, the ethylene generation from ReTain™-treated trees was significantly lower than that from control trees. We hypothesized that delayed floral senescence was a consequence of decreased ethylene generation; however, the visual inflorescence rating data suggested the opposite. The senescence ratings of treated trees were significantly higher than the control trees, indicating ReTain™ increased the rate of flower senescence. Throughout the experiment, the first-opened flowers senesced first.

The blocks on the edge of the orchard senesced earlier than blocks in the center of the orchard, east sides of the rows than the west, and the south end of the rows earlier than the north. The flowers in the row on the edge of the orchard and the ones on the south end of the rows also bloomed first. This could be potentially explained by that those flowers were at locations to receive the most heat. The visual evaluation of inflorescence senescence was based on petal color change and petal drop. It might not indicate the ovule viability throughout the experiment. Therefore, it is possible that the petal drop was not correlated with the effective pollination period and ovule viability. Aniline blue fluorescence was argued to be an accurate method to measure ovule senescence in olives The findings on pollen tube growth supports this possibility. There was no significant difference between treated and control flowers in pollen tube width. This suggested both treated and control flowers were pollinated equally, even though the treated flowers senesced more rapidly than the control flowers. The non-significant difference in pollen tube width suggested that pollination an ovule viability were not affected by ReTain™. It is possible that pollen tube width is not a good indicator of pollination. The pollen tube width is primarily a measurement of the amount of pollen deposited on the stigma that germinated and produced a pollen tube. We selected this measurement reasoning that a longer effective pollination period provides more time for pollen grains to land on the stigmas. Determining whether the pollen tube has reached the ovary might be a better indicator of successful pollination . However, after reaching the ovary, the pollen tube was unrecognizable . The tissue in the ovary was too thick to observe under a fluorescence microscope. In Arabidopsis, both ethylene-dependent and ethylene-independent pathways are required to initiate and progress through floral senescence . It is possible that the floral senescence in olives is not regulated primarily by ethylene. Pollination induces a series of post-pollination developmental events, including petal senescence . Pollination-triggered senescence has multiple advantages. Once sufficient pollen has been set on the stigma, additional pollen deposition is wasteful, and excess pollen tubes may compete for nutrients. In addition, maintenance of floral structures is costly . In 2020, the ReTain™ treatment was applied to two different orchards at the same concentration. However, no ethylene was detected from either treated or control flowers, which may be due to reduced number of flowers in an “off” year. In 2019, heavy rain during bloom could have prolonged the flowering time. The heavy rain and low temperature combined with the spray of ReTain™, while the control rows were not sprayed, could potentially explain the earlier senescence of the treated rows. The lowest temperature during the bloom reached 8°C, while the optimal temperature for olive pollen germination and pollen tube growth is 20 to 25°C . The low temperature during the bloom may have negatively impacted pollination in both ReTain™-treated and control trees. In 2019, the difference in yield between ReTain™-treated and control rows was not significant at 0.05 but was significant at 0.1. However, yield fluctuated greatly in treated rows, while the yield among control rows was stable. ReTain™ strongly improved yield in five out of six rows, but the increase was not consistent and the effect of ReTain™ was not uniform among rows .

This is a two-fold improvement when compared to previous transcriptomic studies

The class II DNA transposons content is 34.0% . This high percentage of class II DNA transposons appear to be present in three lineages of rust fungi, the Melampsoraceae , Pucciniaceae and Phakopsoraceae . The recently assembled large genome of the rust fungus Austropuccinia psidii in the family Sphaerophragmiaceae, however seems to mainly have expanded in retrotransposons. This illustrates that TEs exhibit different evolutionary tracjectories in different rust taxonomical families. Over 80% of the P. pachyrhizi genome is comprised of only two superfamilies of TEs: long terminal repeat and terminal inverted repeat . The largest single family of TE are the Gypsy retrotransposons comprising 43% of the entire genome . To understand the evolutionary dynamics of the different TE families present in the P. pachyrhizi genome, we compared the sequence similarities of TEs with their consensus sequences in the three genomes, which ranges from 65 to 100% sequence identity . Based on the concept of burst and decay evolution of TEs, the extent of sequence similarity between each TE copy to its cognate consensus is proportional to the divergence time of copies. This approach allows us to compare within-genome relative insertion ages of TE insertions using consensus of TE families, a proxy for the ancestral sequence. TEs were categorised as conserved TEs , intermediate TEs and divergent TEs. The average TE composition of the three isolates is 13.2−18.3% conserved, 29.4–29.9% intermediate and represent 51.7−57.3% divergent . The average Gypsy retrotransposon composition of the three isolates is 16.5–20.7% conserved, 30.4–31.03% intermediate, and 48.8–52.5% divergent . Similarly, average TIR composition of the three isolates is 12.2–18.4% conserved, 29.0–29.7 % intermediate and 51.8–57.8% divergent . This suggests that i) multiple waves of TE proliferation have occurred during the history of the species, ii) the invasion of the two major TE families into the P. pachyrhizi genome is not a recent event, and iii) the presence of conserved TEs indicates ongoing bursts of expansion of TEs in the P. pachyrhizi genome.

Therefore,berry pots the proportion and distribution of TEs indicate that different categories of TEs differentially shaped the genomic landscape of P. pachyrhizi during different times in its evolutionary history . We set out to date the Gypsy and Copia TEs in P. pachyrhizi, using a TE insertion age estimation. We observe that most retrotransposon insertions were dated less than 100 million years ago . We, therefore, decided to perform a more granulated study taking 1.0 million year intervals over this period. We approximated the start of TEs expansion at around 65 Mya after which the TE content gradually accumulates . We can see a more rapid expansion of TEs in the last 10 Mya, indeed over 40% of the Gypsy and Copia TEs in the genome seem to have arisen between today and 5 Mya . The climatic oscillations during the past 3 Myr are well known as the period of differentiation for multiple species. Therefore, the genome expansion through waves of TE proliferation in P. pachyrhizi correlates with periods in which other species, including their host species the legumes started their main radiation, and differentiation due to external stressors. This suggests that TEs either play an important role in generating the variation needed to adaptation of various stressors and/or proliferation of TEs is triggered by stressful events. Although a clear causal and or mechanistical role of TEs in adaptation, like in many other systems is still lacking, it is clear TEs have had a major impact on the architecture of the P. pachyrhizi genome.To build a high-quality resource that can facilitate future in-depth analyses, within the consortium, we combined several robust, independently generated RNAseq datasets from all three isolates that include major soybean infection-stages and in vitro germination . Altogether, eleven different stages are captured with seven having an overlap of two or more isolates, representing a total of 72 different transcriptome data sets . These data were used to support the prediction of gene models with the de novo annotation pipeline of JGI MycoCosm. Those proteins secreted by the pathogen that impact the outcome of an interaction between host and pathogen are called effectors and are of particular interest We used a variety of complementary methods to identify 2,183, 2,027, and 2,125 secreted proteins encoded within the genome assembly of K8108, MT2006 and UFV02, respectively.In P. pachyrhizi, depending on methodology, 36.73 − 42.30% of these secreted proteins are predicted to be effectors . We identified 437 common secreted proteins that are differentially expressed at least in one time-point in planta, of which 246 are predicted to be effectors providing a robust set of proteins to investigate in follow-up functional studies . We performed expression analysis on the annotated TEs and observed that 6.66−11.65% of TEs are expressed in the three isolates .

We compared the TE expression from different infection stages versus in vitro stages and used the in planta RNAseq data from the isolates K8108 and UFV02. A relatively small subset of TEs are expressed during the early infection stages between 10 to 72 hours post-inoculation . Remarkably, for this subset, we observed a 20 to 70- fold increase in the expression when compared to the spore and germinated-spore stages, with the expression levels reaching a peak at 24 HPI . To estimate the impact of the insertion age of this in planta-induced TE subset, we performed expression analysis on the conserved, intermediate, and divergent TEs. Although there is a slight overrepresentation of the conserved TEs, several intermediate TEs and divergent TEs are also highly expressed during 10–24 HPI . To compare the expression profile of this subset of TEs to the predicted effectors, we used the 246 core effectors and compared these with 25 known and constitutively expressed housekeeping genes across three isolates. We found that both TE and effector expression peaked at 24 HPI . While expression of effectors remained higher than the 25 selected housekeeping genes during infection, expression of TEs started to be repressed after 72 HPI . This observation would corroborate the hypothesis of stress-driven TE derepression observed in other patho-systems. However, it also shows that in P. pachyrhizi only a small percentage of the TEs are highly expressed during early infection stages. In several different phytopathogenic species a distinct genomic organization or compartmentalization can be observed for effector proteins. For example, the bipartite genome architecture of Phytophthora infestans and Leptospheria maculans in which gene sparse, repeat-rich compartments allow rapid adaptive evolution of effector genes. Other fungi display other organizations such as virulence chromosomes or lineage-specific regions. However, when interrogating both genomic location and genomic distribution of the predicted candidate effector genes in P. pachyrhizi, we could not detect an analogous type of organization . In addition, we did not observe evidence of the specific association between TE super families and secreted protein genes , as has been observed in other fungal species. Additional analyses comparing the distance between BUSCO genes and genes encoding secreted proteins also showed no specific association . Therefore, despite the large genome size and high TE content of P. pachyrhizi, its genome appears to be organized in a similar fashion to other rust fungi with smaller genome sizes. The lack of detection of a specific association between TE and genes in P. pachyrhizi may be due to the level of TE invasion with 93% TE observed for this genome.Rust fungi are dikaryotic, therefore variation can exist both between isolates and between the two nuclei present in each cell of a single isolate. Long-term asexual reproduction is predicted to promote divergence between alleles of loci,hydroponic grow system which in principle can increase indefinitely. Some rusts can reproduce both sexually and asexually leading to a mixed clonal/sexual reproduction. In the rust fungus P. striiformis f.sp. tritici, asexual lineages showed a higher degree of heterozygosity between two haploid nuclei when compared to the sexual lineages.

In the case of P. pachyrhizi, there are clear indications that the population is propagating asexually in South America based on early studies using simple-sequence repeats and internal transcribed spacer sequences. Our data utilizing high coverage raw Illumina data corroborate these earlier studies as we observed high levels of heterozygosity; 2.47% for UFV02, 1.61% for K8108 and 1.43% in MT2006, respectively . This was further corroborated by mapping the Illumina reads to the genome assembly. In total, 283.355, 359.939, and 458.719 SNPs were identified from K8108, MT2006 and UFV02, respectively. The average heterozygous SNPs across the genome is 2.97 SNPs per Kb in UFV02 compared to 2.58 and 3.34 SNPs per Kb in K8108 and MT2006, respectively . We subsequently studied the structural variation as well as the haplotype variation between the three isolates. Remarkably, the structural variation between the haplotypes of UFV02 is 163.3 Mb, while the variation between the complete genomes of the three isolates is 8 to 13 Mb . For example, the total number of repeat expansion and contractions is 7 and 16 times higher between the haplotypes than the variation between the isolates . To look at this inter-haplotype variation in more detail, we selected contigs larger than 1 Mb to study large syntenic blocks between isolates and haplotigs. The largest of these contigs, the 1.3 Mb contig 148 from UFV02 has synteny with contig 5809 from K8108, and contigs 220 and 362 from MT2006 , but not with its haplotig genome counterpart within UFV02, which indicates lack of recombination between haplotypes. This corroborates earlier studies that in South America P. pachyrhizi reproduces only asexually. Collection of the monopustule isolates K8108, MT2006, UFV02 is separated in both time and geographical location . To study SNP variation, we mapped the Illumina data of all three isolates to the reference assembly of UFV02. Given the high level of heterozygosity and TE content, we focused our analysis on the now annotated exome space . After removal of SNPs shared between either all three or two of the isolates, we identified only three nonsynonymous mutations unique for K8180, eight non-synonymous mutations for MT2006 and five unique non-synonymous mutations forUFV02. For these 16 predicted genes, we found evidence for expression in our transcriptome analyses for ten genes. This total number of non-synonymous mutations within exons between the isolates may appear counterintuitive given the time and space differences between collection of these isolates. Nonetheless, it is likely that other single pustule isolates identified from another field would yield a similar number of mutations. Approximately 6 million spores may be produced per plant in a single day resulting in 3 × 1012 spores per hectare per day. Therefore, the ability to generate variation through mutation cannot be underestimated. We observed an enrichment of mutations in the upstream and downstream regions of protein-coding genes , similar to other rust fungi. In contrast to the low number of mutated exons, the number of uniquely expressed genes between the three isolates is relatively high when compared to the core set of differentially expressed genes . This may reflect a mechanism in which transcriptional variation is generated via modification of promotor regions which would have the advantage that coding sequences that are not beneficial in a particular situation can be “shelved” for later use. This would result in a set of differentially transcribed genes for different isolates, and a core set of genes that are transcribed in each isolate.We subsequently set out to identify expanding and contracting gene families within P. pachyrhizi. To this end, a phylogenetic tree of 17 selected fungal species was built using 408 conserved orthologous markers. We estimated that P. pachyrhizi diverged from its most recent common ancestor 123.2−145.3 million years ago , a time frame that coincides with the evolution of the Pucciniales. We derived gene families including orthologues and paralogues from a diverse set of plant-interacting fungi and identified gene gains and losses using computational analysis of gene family evolution. Genomes of rust fungi including P. pachyrhizi underwent more extensive gene losses than gains, as would be anticipated for obligate biotrophic parasites . In total, we identified 2,366 contracted families and 833 expanding families within UFV02, including 792 and 669 families with PFAM domains, respectively. The most striking and significant contraction in the P. pachyrhizi genome is related to DEAH helicase which is involved in many cellular processes, e.g., RNA metabolism and ribosome biogenesis . In contrast, significant expansions in 12 gene families were found, including genes encoding glutamate synthase, GMC oxidoreductase and CHROMO domain-containing proteins .

Both variables showed a close match between simulated and measured values

The first scenario consisted of applying the same amount of fertilizer spread across all irrigation pulses , except for the last irrigation pulse to enable flushing. The second scenario consisted of continuous irrigation of the same duration and irrigation amount as under pulsed treatments, with fertigation at all times , except for the same period of flushing at the end of irrigation. The fertigation scheme in PF1, PF2, PF3 and continuous scenarios was assumed to start from 17 August 2010. All fertigation simulations were run as for the irrigation experiment, that is for 29 days .The water content distribution in the soil reflects water availability to plants, and plays a crucial role in water movement through and out of the root zone. Volumetric water contents simulated by HYDRUS 2D/3D are compared in Fig. 5 with the measured values obtained using EnviroSCAN probes 15 cm away from the dripper. Simulated values matched measured values well, both spatially and temporally. However, deviations between simulated and measured values were observed at day 19 of simulation, particularly in the upper 50 cm of the soil profile; at later times this difference was not observed. Simulated and observed daily and cumulative drainage are compared in Figs. 6 and 7, respectively. It can be seen that simulated daily drainage remained slightly below observed values , except for the initial higher leaching on day 1. However,vertical hydroponic nft system the total drainage observed in the lysimeter was matched closely by the model.

The high peak on day represents the effect of high rainfall on that day, which also was very well predicted by the model. However, the cumulative drainage remained slightly over predicted during the initial 15 days, after which the simulated and observed values matched well. Model evaluation was performed using a number of model performance parameters calculated using measured and model generated soil water contents . The mean absolute error varied from 0.006 to 0.22 cm3 cm−3 and the root mean square error ranged between 0.007 and 0.028 cm3 cm−3, which indicated small deviations between measured and simulated values. However,the maximum values of MAE and RMSE were observed at day 19, confirming the deviations shown in Fig. 5 at this time. However, the values of paired t-test between measured and simulated water contents showed insignificant differences at 5%level of significance at all times.Values of the coefficient of determination varied between 0.68 and 0.96, indicating a reliable generation of water contents by the model at all days of simulations. Similarly, the Nash and Sutcliffe efficiency coefficient values ranged from 0.17 to 0.96, indicating a good performance of the model for the prediction of water contents in this study.However,the relative efficiency value at day 19 reveals unsatisfactory performance of the model at that point according to the criteria suggested by Moriasi et al. . The values of MAE, RMSE, r2, E, and RE for the drainage flux were 2.87, 4.14, 0.97, 0.94, and 0.78 , respectively, which also showed a robust performance of the model for drainage fluxes from the lysimeter. The close match of both water contents and drainage fluxes indicates that the HYDRUS 2D/3D software can be successfully used to predict water movement and drainage fluxes in a lysimeter planted with a citrus tree. Other studies have also reported good performance of this software for various soil, water, and crop conditions under pressurised irrigation systems . Simulated water balance components over the 29 day experimental period are shown in Table 3. It can be seen that simulated drainage, which is similar to the amount measured in the lysimeter, represents 48.9% of the total water balance.

A much higher seasonal drainage has been reported for a lysimeter planted with an orange tree in a fine sandy soil . High drainage is bound to occur in highly permeable, coarse textured soils, such as the sand/loamy soil used in this study, where water drains easily and quickly from the root zone because gravity dominates over capillarity . However, Sluggett estimated deep drainage in the range of 6.1–37.2% under citrus trees growing in light textured soils in the Sunraysia region of Australia. A major contributor to the high drainage measured in this experiment was the high amount of water applied, mostly as a result of large rainfall events. Simulated plant water uptake was estimated to be 40% of the water application, indicating low irrigation efficiency of the drip system. The daily plant uptake varied from 1.2 to 3.14 mm . However, plant uptake is a very complex process, and depends on a number of parameters describing the root and canopy development. Since the HYDRUS model does not support a dynamic behaviour of the root system and considers only the static root parameters, root uptake was optimised on the basis of a changing transpiration rate over time. Additionally, since in the present study we dealt with a tree, for which the root distribution development over time is not as fast as observed for seasonal crops like cereals, the root development was considered relatively constant for the modelling purpose. Hence, a static root distribution and variable atmospheric conditions produced a good approximation of plant uptake, as has been revealed in a number of earlier studies that used HYDRUS for modelling purposes Simulated distribution of nitrate at selected times after commencement of fertigation is shown in Fig. 8. Concentration of NO3-N was maximum at the centre of the plume below the dripper, with a gradual decrease in N concentration towards the outer boundaries of the plume. Subsequent irrigation and fertigation pulses resulted in enlargement of the plume, with a rapid lateral and vertical movement of NO3-N. It is worth noticing that after 15 days of fertigation all nitrate still remained in the lysimeter, reaching a depth of 70 cm. The maximum nitrate concentration at this time was at 20 cm. The simulated NO3-N uptake accounted only for 25.5% of applied nitrogen .

The remaining nitrogen was still available in the soil for plant uptake, provided it was not transformed by soil biological processes. No nitrate leaching was predicted by the model within this initial 15 day period. The total seasonal recovery of applied N amounts to 42.1% by the orange tree, while 7.7% of added NO3-N was retained in the soil atthe end of the season. These results agree with the findings of Paramasivam et al. who reported 40–53% nitrogen uptake in afield experiment on citrus. Similarly, Boaretto et al. showed 36% recovery of applied nitrogen by an orange tree in a lysimeter. The seasonal distribution of nitrate in the soil at 30-day intervals after the fertigation commencement is shown in Fig. 9.It can be seen that nitrate rapidly moved downwards and dispersed in the lysimeter, reaching a depth of 95 cm after 30 days. However, the zone of the maximum concentration remained close to the soil surface. Subsequent fertigation pulses further pushed N near to the leaching outlet at 60 days and N dispersed throughout the lysimeter, beyond which regular N leaching was observed with subsequent fertigations. However, the concentration of N remained much higher in the upper soil depth till 180 days of fertigation, enabling its continued uptake by the orange tree. The nitrogen concentration thereafter reduced drastically in the upper zone as a result of the withdrawal of fertigation after 195 days of simulation . At 210 days after commencement of fertigation ,nft hydroponic system the NO3-N concentration in the domain ranged between 0 and 0.4 mg cm−3, and continued to decline until it completely moved out of the upper 40 cm soil depth at 270 days. At the end of the simulation , only a very small amount of nitrate remained in the lysimeter, with higher concentration occurring at the bottom of the lysimeter , indicating higher vulnerability of this N to leaching. Major leaching of NO3-N took place after 90 days of simulation, amounting to 61%of total N leaching between 90 and 180 days , which corresponds to heavy precipitation of 95 mm on day 115 and 68 mm on day 152 of simulation. Paramasivam et al. and Nakamura et al. also reported that unexpectedly prolonged irrigation or high rainfall following fertilizer applications led to higher NO3-N leaching losses.

Total nitrate leaching amounted to 50.2% of the N applied as fertilizer . Nitrate losses of similar magnitude have also been reported by Syvertsen and Sax and Boman and Battikhi in a lysimeter grown orange tree. On the other hand, low NO3-N leaching losses ranging from 2 to 16% of the applied nitrogen have been reported in some studies on citrus . The migration of nitrate to deeper layers is highly dependent on the amount of irrigation and rainfall, as this is the driving force moving nitrate out of the root zone. Lower nitrate leaching estimated in this study may have been a consequence of improved irrigation and fertilizer management through the drip system. Hence improved water efficiency under drip irrigation, by reducing percolation and evaporationlosses, can contribute considerably towards environmentally safer fertilizer applications . In addition to the factors discussed above, a choice of appropriate source, amount, frequency, and timing of fertilizer applications and the rate of N transformation into NO3 are other important factors that determine the amount of NO3-N leaching out of the vadose zone .Temporal distribution of nitrate for different fertigation scenarios is presented in Fig. 11.Although nitrate movement appears to be similar in all scenarios, small differences can be observed in nitrate distribution in the soil for some scenarios. In scenarios PF and PF3, in which fertilizer was applied with all pulses in low concentrations or towards the end of irrigation, the N concentration after 2, 7, and 14 days was slightly higher in the centre of the plume where root activity was at a maximum. However, the nutrient uptake varied within a narrow range under normal irrigation , indicating an insignificant impact of fertigation timing under conditions experienced in our lysimeter study. Contrary to this, Hanson et al. reported 14% higher nitrate uptake when fertilizer was applied at the end of the irrigation event in a HYDRUS simulation that was based on historical irrigation and fertigation data. A similar observation was also made by Paramasivam et al. and Alva et al. in field experiments. Gärdenäs et al. also concluded that fertigation applied towards the end of the irrigation cycle generally reduces the potential for nitrate leaching under micro-irrigation systems, with the exception of clayey soils.A short fertigation pulse used in our study, as compared to the other studies, may have reduced differences among various scenarios. However, these results imply that fertigation in a short pulse towards the end of the irrigation event or low concentration fertigation with all pulses could increase the efficiency of nitrogen fertigation as compared to other options. Nitrate distribution in the domain after 21 and 28 days were similar in all scenarios , and all differences disappeared by 21 days of simulation. It can be shown that while nitrate distribution varied during one application phase, they were similar for all scenarios at the end of each irrigation cycle. Also, nitrate moved to a similar soil depth after 28 days in all scenarios. These scenarios did not produce any NO3-N leaching because of the short simulation period. A comparison of nitrate uptake between pulsed and continuous irrigations revealed that scenarios with pulsed irrigation had almost alike nitrate uptake as fertigation with continuous irrigation. Similar results were obtained in scenarios with different irrigation quantities. A negligible impact of pulsing on moisture distribution pattern and drainage has been reported in earlier studies for different dripper discharge rates and spacings . This observation further confirms that pulsing has little impact on solute distribution in the soil under optimal irrigation applications as compared to continuous irrigation.Modelling simulations were also performed to evaluate the impact of variable irrigation applications on nitrate movement for scenarios discussed above . It can be seen that plant NO3- N uptake gradually reduced as the amount of irrigation increased. The nitrogen uptake efficiency for the 50% irrigation treatment varied from 55.3 to 56.2% for all scenarios of fertilizer applications, which was about 8.5% higher than uptake recorded for the normal irrigation . On the other hand, a higher amount of irrigation than normal reduced nitrate uptake of an orange tree by further 3.4–3.6%. At the same time, the zone of maximum nitrate concentration moved to a depth of 40–60 cm , where root uptake decreased exponentially due to the reduction in root density.

How Often To Run Pump On Nft System

In an NFT hydroponic system, the pump should run continuously to maintain a consistent flow of nutrient solution over the roots of the plants. The continuous flow ensures that the plants receive a constant supply of water and nutrients while allowing for proper oxygenation of the roots.

Running the pump continuously helps prevent the roots from drying out and ensures a consistent nutrient delivery. It also aids in maintaining a stable root zone temperature. The continuous flow of nutrient solution in the NFT channels creates a thin film of liquid that flows over the roots, providing them with the necessary moisture and nutrients.

Therefore, it is recommended to run the pump in an NFT system 24 hours a day, seven days a week. This ensures that the plants receive a consistent supply of nutrient solution and promotes healthy growth. However, it’s important to monitor the nutrient solution levels and the overall health of the plants regularly to ensure optimal conditions and make any necessary adjustments.

Ways To Grow Hydroponic Cucumbers

Cucumbers can be successfully grown using various hydroponic methods. Here are a few ways to grow hydroponic cucumbers:

  1. Nutrient Film Technique (NFT): Cucumbers thrive in NFT systems. Set up sloped channels or troughs for the plants to sit in, allowing a thin film of nutrient-rich water to flow continuously over the roots. Ensure proper support for the cucumber vines as they grow, as they can become heavy.
  2. Deep Water Culture (DWC): DWC is another suitable method for growing cucumbers hydroponically. Use floating rafts or platforms to support the cucumber plants with their roots submerged in the nutrient solution. Oxygenate the solution adequately to promote healthy root growth.
  3. Drip System: Drip irrigation works well for cucumbers. Place drip emitters near the base of each plant, providing a slow and steady supply of nutrient solution directly to the root zone. This method ensures efficient nutrient delivery while avoiding excessive moisture.
  4. Aeroponics: Although less commonly used for cucumbers, aeroponics can be experimented with. Suspended cucumber roots in air and periodically mist them with a nutrient solution. Ensure that the mist droplets reach the roots for nutrient absorption.
  5. Tower Gardens or Vertical Systems: Cucumbers can be grown in vertical hydroponic systems, utilizing tower gardens or stacked layers. These systems optimize space by growing plants vertically and provide support for the cucumber vines to climb as they grow.
  6. Greenhouse Hydroponics: Hydroponic cucumber production is often done in controlled greenhouse environments. Greenhouses offer ideal conditions, including temperature and humidity control, for cucumbers to thrive. Various hydroponic systems, such as NFT or DWC, can be implemented within a greenhouse setup.

Remember to select cucumber varieties suitable for hydroponic cultivation, maintain proper nutrient balance, monitor pH and EC levels, provide adequate support for the plants, and ensure proper lighting and ventilation for optimal growth.

25 Litre Large Plastic Container Plant Pots

25-litre large plastic container plant pots are ideal for accommodating plants that require more space for root development or have larger root systems. These pots are commonly used for growing trees, shrubs, and other sizable plants. Here are some key features and considerations regarding 25-litre large plastic container plant pots:

  1. Size: With a capacity of 25 litres, these pots provide ample room for plants to establish a healthy root system and grow to a significant size.
  2. Material: The pots are typically made of durable plastic, such as polypropylene or high-density polyethylene (HDPE), that is resistant to cracking, breaking, and UV degradation. This ensures their longevity and suitability for outdoor use.
  3. Drainage: Adequate drainage is crucial for plant health. Look for pots with sufficient drainage holes at the bottom to prevent waterlogging and promote healthy root growth.
  4. Stability: Larger pots tend to be heavier, providing increased stability and resistance to tipping over in windy conditions. However, keep in mind that once filled with soil and plants, these containers can be challenging to move.
  5. Portability: While these pots may be heavier and less portable than smaller options, they can still be moved with some effort. Consider placing them on plant caddies or using pot trolleys to facilitate transportation when necessary.
  6. Reusability: Plastic containers are reusable and can be used for multiple planting seasons. Proper cleaning and disinfection between uses are recommended to prevent the spread of diseases or pests.
  7. Maintenance: Plastic pots are relatively low-maintenance. They are easy to clean and maintain, and they resist fungal growth. However, over time, they may show signs of wear and tear, and if they become damaged, replacement may be necessary.

When purchasing 25-litre large plastic container plant pots, you can find them at garden centers, nurseries, or online gardening stores. Consider the specific needs of the plants you intend to grow and ensure that the pot size aligns with their growth requirements.

How Much Land is Required for a Profitable Blueberry Farm

The amount of land required for a profitable blueberry farm can vary depending on several factors, including the blueberry variety, planting density, management practices, market demand,25 liter plant pot and the scale of your operation. Here are a few considerations to help you estimate the land requirement:

  1. Planting Density: Blueberries can be planted at different densities, ranging from 1,000 to 3,000 plants per acre (2,500 to 7,400 plants per hectare) or even higher for some high-density systems. The planting density you choose will depend on factors like the variety, management system (conventional or high-density), and intended yield.
  2. Yield per Plant: The yield per blueberry plant can also vary based on various factors, such as age, variety, pruning, fertilization, and overall management. It’s essential to consider the potential yield per plant to estimate the overall yield and profitability of your farm.
  3. Market Demand: Assess the local market demand for blueberries. Consider factors such as consumer preferences, competition, and potential market outlets (wholesale, direct-to-consumer, value-added products). Understanding the market demand will help determine the quantity of blueberries you need to produce and the scale of your operation.
  4. Profitability Analysis: Conduct a comprehensive profitability analysis to estimate the revenue and expenses associated with blueberry farming. Consider costs related to land acquisition or lease, plants, labor, equipment, irrigation, fertilizers, pest management, marketing, and other operational expenses. This analysis will help you determine the scale of the operation required to achieve profitability and the corresponding land area.
  5. Crop Rotation and Diversity: Blueberries benefit from crop rotation to manage soil health and reduce disease pressure. Plan for crop rotation and consider the land area required for this purpose.
  6. Expansion Potential: Consider your long-term goals and the potential for expanding your blueberry farm. If you plan to expand in the future, it’s advisable to secure land that can accommodate your future growth.

It’s challenging to provide an exact land requirement as it varies depending on several factors. However, as a rough estimate,square plant pots a small-scale blueberry farm with around 1-2 acres (0.4-0.8 hectares) can be a starting point for a profitable operation. Larger commercial blueberry farms can span tens or hundreds of acres (hectares) or more.

It’s crucial to conduct thorough market research, feasibility studies, and consult with local agricultural extension services or experienced blueberry growers in your area to get more precise estimates based on your specific circumstances and goals.