Category Archives: Agriculture

Nitrous oxide emissions alone accounted for approximately 26% of the total

However if the timing and controls on hot moments are unknown or sporadic, less frequent sampling may significantly underestimate N2O emissions . Our results suggest that roughly 8,000 randomized individual chamber flux measurements would be needed to accurately estimate annual N2O budgets from these agricultural peat lands with a 95% confidence interval and 10% margin of error, assuming the drivers of hot moments were not well understood. Approximately 500 individual measurements would yield a 50% margin of error. Given the more sporadic nature of CH4 hot moments, our results suggest that it is even more difficult to accurately estimate CH4 fluxes with periodic sampling in these ecosystems. Analyses found that at least 17,000 and 2,500 individual flux measurements would be needed to estimate annual CH4 budgets within a 10% and 50% margin of error, respectively. The agricultural maize peat land soil studied here was a much larger source of soil GHG emissions than other maize agroecosystems. While agricultural peat soils are highly productive, average annual GHG emissions were 3.6-33.3 times greater on an area-scaled basis and 3-15.6 times greater on yield-scaled basis relative to other agricultural maize emissions estimates. We conducted an upscaling exercise as a first approximation of the potential impacts of maize peat land fluxes on regional GHG budgets. Our estimates suggested that maize agriculture on similar peat soils in the region could emit an average of 1.86 Tg CO2e y-1 .This value is significantly higher than previous estimates for the region and highlights the importance of including high frequency N2O measurements to capture hot moments in N2O fluxes,plastic pots 30 liters the disproportionate impact N2O emissions have on agricultural peat land GHG budgets, and that these agricultural peat lands are significant N2O sources.

We also found that irrigation timing and duration, not fertilization, was the predominant driver of N2O and CH4 emissions and a significant source of the total GHG budget. Determining management strategies that reduce soil N2O and CH4 emissions, particularly changes in flood irrigation timing and duration, could have a disproportionate impact on reducing total agricultural peat land GHG emissions .Although legends of humans using coffee in Ethiopia date back as early as 875 A.D., the earliest verifiable evidence of human coffee consumption occurs in Yemen in the 15th century. At this time, it was illegal to bring unroasted coffee out of Arabia, and strict measures were taken to ensure that viable coffee seeds did not leave the country. The birth of coffee production in India is attributed to the Indian Muslim saint Baba Budan, who, on his return from a pilgrimage to Mecca, allegedly smuggled seven coffee beans out of Arabia by hiding them in his beard. In 1670 he planted these seeds in Karnataka, and cultivation soon spread throughout the state and into neighboring regions. The first large-scale plantations arose with British colonization and spread rapidly throughout South India, fueled by increasing demand for export to northern latitudes. The proliferation of coffeehouses in Western Europe during this era proved to have substantial social consequences. Also known as “Penny Universities” since the price of entry and a cup of coffee was commonly one penny, coffeehouses in 17th century Britain came to play an important role in social and political discourse. In a society with such a rigid socioeconomic class structure, coffeehouses were unique because they were one of the only places frequented by customers of all classes.Thus they became popular establishments for discourse and debate, open to all classes and unfettered by the structure of academic universities. Intellectuals found in “the hot black liquor a curious stimulus quite unlike that produced by fermented juice of grape.”English coffeehouses “provided public space at a time when political action and debate had begun to spill beyond the institutions that had traditionally contained them,” and because of this, are widely accepted as playing a significant role in birthing the age of Enlightenment in Europe.While coffee was bringing the Enlightenment to Western Europe, the commodity was having opposite effects in the regions where it was being produced.

In India, the age of British plantations was rife with suffering and oppression, as slavery and forced labor were common practice. Historical research reveals that “during Europe’s industrial revolution and rise of bourgeois society, slavery, coffee production, and plantations were inextricably linked.”Historical records indicate that in the 1830s, the East India Company held over 247,000 slaves in Wayanad the Malabar coast alone.Even after slavery was officially abolished in 1861, so-called “agricultural slavery” and indentured labor on plantations continued. 8 According to historical accounts, indentured laborers were treated almost identically as they were during the height of slavery. To this day, an estimated 18.3 million people in India and 46 million people worldwide live in conditions of modern defacto slavery, such as bonded labor, human trafficking, and forced marriage. The global coffee market has always been volatile. Plagued by unpredictable harvests, susceptibility to weather events, and massive disease outbreaks, regional coffee production has risen and fallen dramatically over the centuries. For example, in the late 19th century in Sri Lanka an outbreak of the fungal pathogen known as “coffee rust” caused 90 percent of area under coffee cultivation on the island to be abandoned. 11 This past century has been no different for India. As the Great Depression affected coffee exports around the world in the 1930s, the Coffee Board of India was established to protect farmers and promote consumption of coffee. The Coffee Board of India, run by the federal government’s Ministry of Commerce and Industry, pooled farmers’ coffee for export at a set price. This provided price stability for farmers but also eliminated incentives to improve quality. From 1991 – 1996 a series of economic reforms relegated the coffee market in India entirely to the private sector. Immediately thereafter, the price of coffee fell from its 1997 levels of around $2.50 per pound to a staggering 45 cents per pound in 2002, the lowest it has been in over fifty years.India was not alone in this plight. While certainly not the only cause of financial insecurity among farmers, the spread of neoliberalism and free trade in the global commodity market has historically been associated with large increases in price volatility and overall downward trends in price, which has had deleterious effects for small-scale producers who depend on these markets for their livelihoods.

Especially in the 1980s and 1990s, growth and consolidation among multinational commodity traders led to a relative loss of market power among producing nations, while foreign pressure from international donors forced many of those nations to privatize their commodity export authorities against their own best interests.This has led to income instability and poverty for many coffee farmers around the world. The coffee farmers of Kerala are facing many of the same challenges that currently plague coffee farmers all over the world. In recent years the global price of coffee has fell drastically from $2.88-per-pound in 2011 to 93 cents-per-pound as of May 2019.While maintaining its downward trend over the past decade, the price continues to fluctuate wildly, making it impossible for farmers to budget their yearly expenses. It is not unheard of for the price to even dip below an individual farmer’s production costs,round plastic pots leaving powerless farmers forced to sell their harvest at a loss, or let it spoil in the fields and get nothing at all. How is it possible that coffee farmers are selling their harvest for less than what it cost them to produce it? While this seems paradoxical to the very basis of economics, it is a common situation facing farmers of many different cash crops, where prices are determined by what are called “buyer-driven supply chains.” While many factors go into the creation of buyer-driven supply chains, some of the few largest factors are discussed below. All this to say, farmers do not have the capacity to determine the price they get for their own products. Prices are driven by market conditions, speculation, futures contracts, and corporate interests who control the majority of world-market shares. With the growth of powerful commodities traders and the liberalization of international markets, prices for coffee and incomes for farmers have reached historic lows. This has led to an increasingly tenuous existence for those who already struggle to get by. Historically, coffee cultivation consisted of only one plant species, Coffea arabica. Today, Coffea arabica still makes up most of the world’s coffee production , but cultivation of another species, Coffea canephora, also known as robusta coffee, is growing due to its higher levels of hardiness and productivity.In addition, a very small amount of a third species Coffea liberica is grown. Although modern coffee production is currently limited to the scope of these three species, a large diversity of sub-varieties and hybrids are grown throughout the world, each with their own unique flavors and characteristics. Coffea arabica is widely lauded as having the best cup quality, and consistently fetches a higher price on the global commodity market. It also tends to grow better in slightly shaded conditions, making it conducive to traditional inter cropping methods.

In India, Coffea arabica is usually grown under the shade of other cultivated trees, such as jackfruit and areca nut, or under the shade of native forest trees, which are used to support vines of black pepper.In the under story below the coffee plants ginger, clove and turmeric are grown. In addition to sustaining families of farmers for generations, a recent study has shown that these multi-species farms support much higher levels of animal biodiversity than conventional monocultures, and that they sequester soil carbon at the same rate as surrounding rain forests. However, the rise of C. canephora as a cash crop has changed things in Kerala. Due to its higher yields and tolerance to pests such as coffee rust C. canephora plantations have replaced multi-species C. arabica farms over huge swaths of India in recent decades. Today, nearly 80% of coffee grown in Wayanad and surrounding regions is C. canephora. Since this robusta species prefers full-sun conditions, this shift away from C. arabica is associated with the removal of shade trees and a proliferation of full-sun monoculture coffee plantations. This has had substantial consequences for biodiversity, erosion, watershed management, and other ecosystem services.This has the potential to negatively impact the small amount of C. arabica that remains in Kerala. Studies indicate that deforestation can lead to a hotter and drier local climate.Coffea arabica is a finicky plant, thriving in a narrow temperature range between 18˚ – 21˚ Celcius.It follows that this pattern of tree removal could lead to conditions in Kerala becoming less ideal for Coffea arabica. This would suggest the potential for a feedback loop, in which robusta production and the associated deforestation lead even more farmers to convert to robusta in order to cope with changing environmental conditions. If climate change is occurring in Kerala, it would not only be threatening cultivated coffee, but also a multitude of wild species. At least six species of wild coffee are known to occur in India.According to a recent study there are now 124 known species of wild coffee, each with their own under-studied and potentially useful characteristics, such as drought or pest resistance, unique flavor profiles, or naturally decaffeinated beans.Of these, an estimated 60% are threatened with extinction due mostly to climate change and habitat loss.The following analysis examines the local climate of Wayanad in recent decades to determine if any changes are occurring. Farmers interviewed during a field visit to Kerala assert that local conditions have become hotter and drier, especially during specific times of the year that are important to the life cycle of the coffee plant. The farmers of Wayanad have suggested an increasingly unpredictable monsoon season, a failure of the “blossom rains” in early spring, and a decrease in November showers. The following study was conducted to corroborate the personal experience of these farmers, and, in the event that trends are found, to determine if causal factors point to global-scale or local forcings. The district of Wayanad in the State of Kerala, India is a mountainous tropical region with altitudes ranging from 700 to 2100m above sea level, daily temperature minimums from 14˚ – 20˚ C, and daily temperature maximums from 25 – 32˚ C.

The application of an appropriate photochemical model could answer this unknown

Although some microorganisms also fix nitrogen, they do not represent significant sources of atmospheric NH3 on Earth. Likewise, the associated detection of N2O and other nitrogen-containing species would provide confidence that the production of NH3 is associated with industrial disruption of a planetary nitrogen cycle. It is worth emphasizing that NH3 or N2O alone would not necessarily be technosignatures, as either of these species could be false positives for life or could arise from nontechnological life . Rather, it is the combination of NH3 and N2O that would indicate disruption of a planetary nitrogen cycle from an ExoFarm, which may also show elevated abundances of NOx gases as well as CH4. The short lifetime of NH3 in an oxic atmosphere implies that a detectable abundance of NH3 would suggest a continuous production source. Although NH3 could be produced abiotically by combining N2 and H2, an atmosphere rich in H2 would be unstable to the O2 abundance required to sustain photosynthesis. The technosignature of an ExoFarm would therefore require the simultaneous detection of both NH3 and N2O in the atmosphere of an exoplanet along with O2, H2O, and CO2.Large-scale agriculture based on Haber–Bosch nitrogen fixation could be detectable through the infrared spectral absorption features of NH3 and N2O as well as CH4. A robust assessment of the detectability of such spectral features in an Earth-like atmosphere would ideally use a three-dimensional coupled climate–chemistry model to calculate the steady-state abundances of each of these nitrogen-containing species a function of biological and technological surface fluxes. But as an initial assessment,hydropopnic barley fodder system we consider a scaling argument to examine the spectral features that could be detectable for present-day and future Earth agriculture.

We define four scenarios for considering agriculture on an Earth-like planet, with the corresponding atmospheric abundances of nitrogen-containing species listed in Table 1. The present-day Earth scenario is based on recent measurements of NH3, N2O, and CH4 abundances . The choice of 10 ppb for NH3 is toward the higher end for Earth today and corresponds to regions of intense agricultural production. The preagricultural Earth scenario serves as a control, where the agricultural and technological contributions of NH3, N2O, and CH4 have been removed. Note that this approach assumes that eliminating the technological contributions to the atmospheric flux of these nitrogen-containing species will reduce the steady-state atmospheric abundance by a similar percentage; this approach is admittedly simplified, but the results can still be instructive for identifying the possibility of detectable spectral features. The third and fourth scenarios project possible abundances of NH3, N2O, and CH4 for futures with 30 and 100 billion people, respectively. Earth holds about 7.9 billion people today, and population projections differ on whether or not Earth’s population will stabilize in the coming century . These two population values were selected because they correspond approximately to the maximum total allowable population using all current arable land and all possible agricultural land . Most published estimates of Earth’s carrying capacity range from about 8 to 100 billion, although some estimates are less than 1 billion while others are more than 1 trillion . Theoretically, an extraterrestrial population with the energy requirements of up to 100 billion calorie consuming humans could sustain Haber–Bosch synthesis over long timescales, as long as sustainable energy sources are used . These scenarios also follow a scaling argument by assuming that the per-person contributions of these three nitrogen-containing species will remain constant as population grows. This again is a simplifying assumption that is intended as an initial approach to understanding the detectability of such scenarios.

We consider the detectability of all four of these scenarios using the Planetary Spectrum Generator . PSG is an online radiative transfer tool for calculating synthetic planetary spectra and assessing the limits of detectability for spectral features that can range from ultraviolet to radio wavelengths. The ultraviolet features of NH3, N2O, and CH4 are strongly overlapping and only show weak absorption, but mid-infrared features of all these species could be more pronounced. The mid-infrared spectral features of NH3, N2O, and CH4 calculated with PSG for preagricultural, present-day, and future Earth scenarios are plotted in Figure 1, which shows the relative intensity and transmittance spectra for observations of an Earth-like exoplanet orbiting a Sun-like star. The spectra shown in Figure 1 show the strongest absorption features due to NH3 from 10 to 12 μm, while N2O shows absorption features from 3 to 5 μm, 7 to 9 μm, and 16 to 18 μm. Absorption features due to CH4 overlap some of the N2O features from 3 to 5 μm and 7 to 9 μm. The change in peak transmittance between 10 and 12 μm for NH3 compared to the preagricultural control case is about 50% for the future Earth scenario with 100 billion people and about 25% for the scenario with 30 billion people. For N2O, the change in peak transmittance between 16 and 18 μm compared to the preagricultural control case is about 70% for 100 billion people and 50% for 30 billion people. The change in relative intensity for the 100 billion people scenario is up to about 10% compared to the preagricultural control case between 7 and 9 μm and 10 and 12 μm. Present-day Earth agriculture would exert a weakly detectable signal that might be difficult to discern from the preagricultural control case, but future scenarios with enhanced global agriculture could produce absorption features that are easier to detect. The spectral features of NH3, N2O, and CH4 could be detectable in emitted light or as transmission features for transiting planets. Specifically, the N2O line at 17.0 μm shows a strong dependency with the N2O volume mixing ratio and to a second order the NH3 line at 10.7 μm. For the future 100 billion case, both display strong enough absorption to bdetectable by the Large Interferometer for Exoplanets , Origins and Mid-InfraRed Exo-planet CLimate Explorer infrared mission concepts.

The James Webb Space Telescope Near Infrared Spectrograph could potentially detect CH4 within the 0.6–5.3 μm range for transiting exoplanets . However, the detection of CH4 alone would provide no basis for distinguishing between technological, biological, or photochemical production. The detectability of these spectral features do not necessarily directly correspond to the peak transmittance, and a full accounting of the detectability of each band would need to account for the observing mode and instrument parameters. It is beyond the scope of this present paper to present detectability calculations for specific missions, as any missions capable of searching for mid-infrared technosignatures are in an early design phase, at best. One of the goals of this Letter is to highlight the importance of examining mid-infrared spectral features of exoplanets,livestock fodder system as many potential technosignatures could be most detectable at such wavelengths. Also, it demonstrates the duality of the search for bio-signatures and technosignatures. The search for passive, atmospheric technosignatures does not require the development of a dedicated instrument but can leverage the capability of instruments dedicated to the search for bio-signatures.The calculations presented in this Letter indicate the possibility of detecting a technosignature from planetary-scale agriculture from the combined the spectral features of NH3 and N2O, as well as CH4. The signature of such an ExoFarm could only occur on a planet that already supports photosynthesis, so such a planet will necessarily already show spectral features due to H2O, O2, and CO2. The search for technosignatures from extraterrestrial agriculture would therefore be a goal that supports the search for bio-signatures of Earth-like planets, as the best targets to search for signs of nitrogen cycle disruption would be planets already thought to be good candidates for photosynthetic life. A better constraint on the detectability of the spectral features of an ExoFarm would require the use of an atmospheric photochemistry model. This Letter assumed simple scaling arguments for the abundances of nitrogen containing species, but the steady-state abundance of nitrogen containing atmospheric species will depend on a complex network of chemical reactions and the photochemical impact of the host star’s UV spectrum. In such future work, the increases of NH3 and N2O, and CH4 from agriculture would be parameterized via surface fluxes instead of arbitrary fixed and vertically constant mixing ratios. A network of photochemical reactions would then determine the vertical distribution of those species in the atmosphere. A photochemical model could also capture the processes of wet and dry deposition of NH3, which is the major sink in Earth’s present atmosphere, as well as aerosol formation from NH3 and SO2/N2O that can occur in regions of high agricultural production. Past studies have predicted more favorable build-up of bio-signature gases on oxygen-rich Earth-like planets orbiting later spectral type stars due to orders of magnitude less efficient production of OH, O, and other radicals that attack trace gases like CH4 .

The photochemical lifetime of N2O and therefore its steady-state mixing ratio will be enhanced by less efficient production of O radicals that destroy it. However, because deposition is the major sink of NH3, it is not clear whether a different stellar environment would alter the atmospheric lifetime of NH3, and if so, to what extent.Examining the four scenarios in this study with such a photochemical model would require additional development work to extend the capabilities of existing models to oxygenrich atmospheres. Past photochemical modeling studies that have included NH3 considered anoxic early Earth scenarios where the focus was determining the plausible greenhouse impact of NH3 to revolve the faint young Sun paradox . More recent studies have considered NH3 bio-signatures in H2-dominated super-Earth atmospheres, which would greatly favor the spectral detectability of the gas relative to high molecular weight O2-rich atmospheres . On H2 planets with surfaces saturated with NH3, deposition is inefficient, and sufficient biological fluxes can overwhelm photochemical sinks and can allow large NH3 mixing ratios to be maintained . These “Cold Haber Worlds” are far different from the O2–N2 atmosphere we consider here, where surfaces saturated in NH3 are implausible and photochemical lifetimes are shorter. Ideally, future calculations would use a three-dimensional model with coupled climate and photochemical processes suitable for an O2–N2 atmosphere to more completely constrain the steady-state abundances, and time variation, in nitrogencontaining species for planets with intensive agriculture. Future investigation should also consider false-positive scenarios for NH3 and N2O as a technosignature. One possibility is that a species engages in global-scale agriculture using manure only; such a planet could conceivably accumulate detectable quantities of NH3 and N2O without the use of the Haber–Bosch process. The distinction between these two scenarios might be difficult to resolve, but both forms of agriculture nevertheless represent a technological innovation. Whether or not similar quantities of NH3 and N2O could accumulate on a planet by animal-like life without active management is a possible area for future work. External factors such as stellar proton events associated with flares could also produce high abundances of nitrogen-containing species in an atmosphere rich in NH3 , so additional false-positive scenarios should be considered for planets in systems with high stellar activity. This Letter is intended to present the idea that the spectral signature of extraterrestrial agriculture would be a compelling technosignature. This does not necessarily imply that extraterrestrial agriculture must exist or be commonplace, but the idea of searching for spectral features of an ExoFarm remains a plausible technosignature based on future projections of Earth today. Such a technosignature could also be long-lived, perhaps on geologic timescales, and would indicate the presence of a technological species that has managed to coexist with technology while avoiding extinction. Long-lived technosignatures are the most likely to be discovered by astronomical means, so scientists engaged in the search for technosignatures should continue to think critically about technological processes that could be managed across geologic timescales. J.H.M. gratefully acknowledges support from the NASA Exobiology program under grant 80NSSC20K0622. E.W.S. acknowledges support from the NASA Interdisciplinary Consortia for Astrobiology Research program. T.J.F and R.K.K. acknowledge support from the GSFC Sellers Exoplanet Environments Collaboration , which is supported by NASA’s Planetary Science Divisions Research Program. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of their employers or NASA.

Detractors warned consumers of substantial food cost increases due to the extremely low threshold

As a result of a practical labeling scheme, the Japanese consumer can purchase non-GM products that are not organic, an option that would all but disappear with Prop 37 in California. Furthermore, in Japan, like in Australia, highly processed products such as canola oil, produced with GM crops, are exempt from labeling. In contrast, the same canola oil would have to bear a cautionary label under Prop 37, in spite of difficulties testing whether the oil has indeed been derived from GM canola. Earlier this year, the American Medical Association formally opposed the mandatory labeling of GM food. The National Academy of Sciences and the World Health Organization previously reached similar conclusions–there is no science-based justification for mandatory labeling of GM food because there is no evidence that such foods pose any risks to human health. Because it will be interpreted as a warning, mandatory labeling would imply a food safety risk that does not exist, and this in itself would be misleading to consumers. If passed, the full economic effects of Prop 37 are uncertain but there is no doubt that the measure would remove most of the certified non-GM processed foods from the California market because of the zero tolerance criterion for low levels of unintended material. Food manufacturers and retailers would be unwilling to supply a large number of both GM and non-GM processed food products due to litigation risk. For instance, there would be a change in the selection of corn flakes boxes on the food shelf. The consumers’ choice would be either organic corn flakes or corn flakes labeled as possibly containing GM. It is believed that 70–80% of processed food intentionally contain some corn,macetas cuadradas canola or soy ingredients, so these products would have to be labeled, reformulated with non-GM substitutes, or removed.

Other processed food products that do not use soy, corn, or canola could also be affected and require labeling, because they might contain unintended trace amounts of corn, canola or soy. As a consequence, Prop 37 would result in many products on the food shelf carrying a GM label. It might get to the point where there are so many products with GM labels that most consumers would just ignore the labels because they would be everywhere. For foods that contain a relatively small amount of corn or soy ingredients, the food industry could either label their products as GM or look for alternative, and possibly inferior, non-GM substitute ingredients to avoid labeling. For instance, food companies would have an incentive to use alternative ingredients such as imported palm oil to replace soybean or canola oil, despite potential health problems associated with palm oil and environmental concerns due to palm oil expansion in Asia. Mandatory labeling requirements could inhibit further development of GM technology in California’s food industry. The United States has criticized the EU’s mandatory GM labeling as being nothing more than international trade protection from foreign competition. In fact, over the last twenty years, the USDA, the FDA and the State Department, under successive administrations from both sides of the political spectrum, have publicly opposed this type of regulation at the international level because of its market distorting effects. Prop 37 may also be interpreted as an attempt to stifle competition and distort markets. In this article we outline the economic implications of GM food labeling programs to provide insight into the likely effects of introducing mandatory labeling of GM foods in California under Prop 37. Supporters of Measure 37 argue that labeling provides California consumers additional information and allows them to avoid consuming GM food. But California food consumers have that choice now. They can purchase from three different food categories: 1) conventional foods , 2) organic foods , or 3) voluntarily labeled non-GM food that is not organic. Compare this current situation to the likely outcome under Prop 37 . For targeted food products derived from GM grains, Prop 37 will most likely replace the existing three food categories listed above with just two categories: 1) organic, or 2) products labeled as “may be produced with genetic engineering.” In other words, there will be numerous GE labeled products.

For highly processed food products, a non-labeled option will remain but may only make sense using either lower grade or more expensive alternative ingredients. In general the organic suppliers will gain market share because the producers of most certified non-GM foods will have to change their label to read “may contain GM,” whereas the organic label will not be forced to change, even if the organic product has the same trace amount of GM as the non-GM counterpart. Since the perunit cost of producing non-GM crops is less than organic crops, overall food prices will rise on average as non-GM food products lose market share.Table 1 summarizes the key features of Prop 37–The California Right to Know Genetically Engineered Food Act. If passed, it will require retail labeling of some raw agricultural GM commodities as being “genetically engineered” and processed foods containing GM ingredients as “ partially produced with genetic engineering.” Exemptions from labeling would be granted to alcoholic beverages, restaurant and ready-made food, foods “entirely” derived from animals, and any food certified as USDA Organic. Also exempt would be any raw agricultural commodity that could be certified that it was produced without the intentional use of GE seed. Furthermore, Prop 37 would prohibit food labels with the message “natural,” “naturally grown,” or anything similar. The initiative charges the California Department of Public Health with enforcement, which the Legislative Analyst Office predicts will cost $1 million annually. Prop 37 sets purity standards for non-GM food that are much higher than existing standards for organic food. Organic certification is “process based,” which means that as long as the farm is an approved organic farm, following the prescribed agronomic practices, there is less industry concern over accidental contamination and therefore no regular testing for GM. Unlike Prop 37, USDA organic standards do not have a strict “zero tolerance” standard for accidental presence of GM material. In fact, the USDA has not established a threshold level for adventitious presence of GM material in organic foods. Organic growers are listed among the coalition of supporters of Prop 37, which is understandable because of the exemption provided to them by Prop 37. If Prop 37 passes, a food product could be labeled as organic and escape the testing and litigation issues facing a similar non-organic product even if both products contained identical accidental trace amounts of GM material. Mandatory labeling is unnecessary because voluntary labeling now gives California consumers a choice to purchase food products that do not contain GMOs . One existing voluntary “GM-free” labeling program is the Non-GMO Project, a verification process organized by food retailers such as Whole Foods Market.

The Non-GMO project uses the same 0.9% threshold as the EU and under this scheme, retailers receive a price premium for selling non-GM products. Whole Foods carries numerous Non-GMO products under its private label, 365 Everyday Value®, and many of these products are also organically produced. Similarly, all food products sold at Trader Joe’s with the Trader Joe’s label are sourced from non-GM ingredients , but they are not part of the Non-GMO project. Like Whole Foods, Trader Joe’s is not actively supporting mandatory labeling of GM foods under Prop 37, perhaps because it would disrupt their product lines. Several processed food products in Trader Joe’s stores that are not privately branded would likely require the new cautionary label under Prop 37,maceta cuadrada plastico not to mention all of the products under the Trader Joe’s line that will not meet the zero tolerance . The issue surrounding Prop 37 is similar to an earlier debate that took place in the 1990s over dairy products from cows treated with rBST . The U.S. FDA ruled that no mandatory labeling of products derived from cows receiving the growth hormone was necessary because the milk was indistinguishable from products derived from untreated herds. Then the state of Vermont passed a law requiring that milk from rBST treated cows be labeled to better provide consumers information. The Vermont legislation was based on “strong consumer interest” and the “public’s right to know.” Dairy manufacturers challenged the constitutionality of the Vermont law under the First Amendment and they won. The Second Circuit Court of Appeals struck down the Vermont law, ruling that labeling cannot be mandated just because some consumers are curious. The court ruled “were consumer interest alone sufficient, there is no end to the information that states could require manufacturers to disclose about their production methods”… “Instead, those consumers interested in such information should exercise the power of their purses by buying products from manufacturers who voluntarily reveal it.” . Instead of mandatory labeling, a non-rBST standard was voluntarily developed by the industry with specifications from the FDA. It has been largely applied to dairy products, giving consumers a choice; but unlike mandatory labeling, producers voluntarily responded to consumer demand for non-rBST milk, following a bottom-up process—it was not a mandate imposed on them by top-down regulations. There are a variety of international mandatory GM labeling programs differing by the products to which they are applied, the mandated adventitious threshold, and whether they apply to the “product” as a whole or to the “process” .

Table 3 summarizes the mandatory labeling laws of a select group of developed nations. As shown in the table, mandatory labeling of GM food exists and is enforced in places like Japan, the EU, South Korea, Australia, and New Zealand. Some developing or transition economies also have mandatory labeling but without strict enforcement. With mandatory labeling, consumers are not necessarily provided with greater choice at the food store. Furthermore, there is a substantial amount of GM food eaten in the EU and Japan that does not have to be labeled. These products include certain animal products, soya sauce and vegetable oils , among others. Internationally, the Codex Alimentarius Commission, an international standards-setting body for food, examined and debated GM food labeling for over twenty years without reaching any consensus. In 2011 a decision was eventually made, but the final text approved by all countries does not provide any recommendation as to the labeling of GM food. It only calls on countries to follow other Codex guidelines on food labeling . This non-endorsement means that countries using mandatory labeling could face legitimate claims of unfair trade restrictions resulting in a World Trade Organization dispute. A labeling initiative similar to California’s Prop 37 appeared on the ballot in Oregon in 2002. This initiative also proposed mandatory labeling, but defined an adventitious threshold of 0.1% per ingredient. Despite a claim of an overwhelming level of public support for GM labeling, the initiative ultimately failed with 70% voting “no.”Additionally, even if the measure had passed, it was unlikely that producers would have segregated GM foods from non-GM, non-organic, as the costs would have been prohibitive—especially for a relatively small state with a population fewer than four million. The bulk of private costs incurred as a result of labeling requirements are from efforts to prevent or limit mixing within the non-GM supply chain, known as identity preservation programs. The cost of any IP program depends critically on the level of the adventitious presence threshold specified in the labeling program. In the case of Prop 37 these costs would be incurred throughout the processed food industry. For instance, a firm marketing a wheat food product would incur costs to ensure its product did not contain trace amounts of soy, canola, or corn, because these grains all use the same grain handling and transport system. The goal of providing consumers with additional information and choice is only met when both product types are carried in food stores. In the EU, companies resorted to substituting ingredients to avoid the label, using lower quality and/or higher priced inputs, something that could also happen in California for processed products. EU consumers were not offered much new information, since no products carried a GM label after the introduction of mandatory labeling. In fact, the EU proponents of labeling are not satisfied with the existing EU regulations because of its exemptions and they have asked for an extension of labeling to include animal products.

Neither of those sources of water is subsidized to any significant degree

This highlights that the method used to define θfc in our study, while objective and tied strictly to soil moisture retention parameters, produced θfc estimates that are relatively conservative from a flow-based definition of θfc, as they are based on how a 1-cm slice of soil would drain. In a soil profile that has been deeply wetted, such as those used in this Ag-MAR modeling study, the defined θfc cannot be achieved by drainage alone within a reasonable time-frame, even at 10-cm depth in a 200-cm sandy loam profile . Thus, the corresponding time-to trafficability estimates should be interpreted as relatively conservative, especially for those soils with low plasticity indices such as sands and sandy loams. This is not to say, however, that the definitions used in this study are outside the norms of soil science. θfc is often defined with a standard tension . All textures but silt loam have estimated θfc values that correspond to this tension range . Finer-textured soils may still have some risk of compaction at the thresholds defined in this study, given their high plasticity indices and the relatively high Ksat estimates produced by the ROSETTA pedotransfer function for these textures . Similarly, while presence of a Bt horizon underlying various surface textures did not consistently delay time-to-trafficability, ROSETTA may overestimate the permeability of 2:1 clay enriched sub-soils occurring on, for example, stable river terraces above current floodplains,hydroponic container system especially in the eastern uplands of the San Joaquin Valley . Thus, these landscapes should be treated more cautiously if used for Ag-MAR during periods when trafficability is required, especially during low PET conditions.

For example, in an Australian study of Vertisol trafficability under irrigated cotton production, researchers concluded that risk-free trafficability only really existed at water contents near wilting point , which is equivalent to about 60% of the mean θfc for clays in our study . On the other hand, this contrasts sharply with a field study in the Netherlands which found that a heavy clay soil under pasture was trafficable at just 90 cm soil moisture tension based on observation of compaction patterns and tensiometer readings , which is moister than the wettest, commonly used tension-based definition of θfc . An additional uncertainty in trafficability and work ability research is the extent to which surficial trafficability and work ability moisture thresholds are sufficient to prevent detrimental subsoil compaction that requires more effort to ameliorate . Field validation studies that include modeling of soil moisture to predict suitable days for agricultural operations and that simultaneously examine full soil profile effects of wheel traffic occurring at or below these moisture thresholds have not yet been reported. A study of controlled traffic farming systems in California cotton production highlights this need, since bulk density increased to 25-cm depth while penetrometer resistance increased to at least 100-cm soil depth under wheel traffic in a sandy loam soil , but no operational decisions were guided by trafficability soil moisture thresholds in their study. Finally, the time-to-trafficability estimates are meant to guide operational decisions when crops are dormant or fields are fallow, given that root water uptake was intentionally neglected and only drainage and bare soil evaporation were considered in H1D simulations. For major perennial crops, end of dormancy typically ranges from mid February to late-April , spanning the time period addressed by this study. There are several reasons for omitting scenarios when root water uptake is active. First, Ag-MAR is recognized to be a risk to many actively growing crops due to the possibility of developing anoxic soil conditions . Second, for deep wetting events more generally, accurate root water uptake modeling requires knowledge of root depth distribution and crop canopy coverage. Third, the need for irrigation water may arise before the soil moisture trafficability threshold during active root water uptake for more sensitive crops or during specific periods of growth.

All of these considerations complicate the ability to provide a generalizable time-to-trafficability tool to growers that also accounts for crop root water uptake.A relationship between global warming and increased concentrations of greenhouse gases such as carbon dioxide , produced by the burning of fossil fuels, is suggested by much accumulating evidence. As far back as 1992, more than 150 governments attending the Rio Earth Summit signed the Framework Convention on Global Climate change. Article 2 states that the ”ultimate objective of this Convention … is to achieve … stabilization of greenhouse gas concentrations that would prevent dangerous anthropogenic interference with the climate system.” More than ten years later, the questions remain: how ”dangerous” are the consequences of anthropogenic interference, and how much ”stabilization” is justified? The economics literature so far has given mixed results with regards to the impact on agriculture.1 In the remainder of this section we give a brief overview of previous approaches to set the stage for our study. These can be divided into three broad categories, beginning with the agronomic approach, based on the use of agronomic models that simulate crop growth over the life cycle of the plant and measure the effect of changed climate conditions on crop yield and input requirements. For example, Adams relies on crop simulation models to derive the predicted change for both irrigated and rainfed wheat, corn, and soybeans. The predicted changes in yields are then combined with economic models of farm level crop choice, using linear or nonlinear programming.The analysis, however, usually considers variable but not fixed costs of production. It often turns out to be necessary to add artificial constraints to make the programming model solution replicate actual farmer behavior in the baseline period. Moreover, the analysis focuses on the agricultural sector, and ignores the linkages with the remainder of the economy which would make the input prices and input allocations to agriculture endogenous.

This is remedied in the computable general equilibriumapproach, which models agriculture in relation to the other major sectors of the economy and allows resources to move between sectors in response to economic incentives. An example is FARM, the eight-region CGE model of the world agricultural economy by the United State Department of Agriculture. However, while a CGE model has the advantages of making prices endogenous and accounting for inter-sectoral linkages, these come at the cost of quite drastic aggregation in which spatially and economically diverse sectors are characterized by a representative farm or firm. In summary, on the one hand the agronomic models do not fully capture the adaptation and mitigation strategies of farmers in the face of climate change, while on the other the CGE models are only appropriate to highly aggregated sectors of the economy. Mendelsohn, Nordhaus and Shaw provide an interesting middle ground, proposing what they call a Ricardian approach, essentially a hedonic model of farmland pricing, based on the notion that the value of a tract of land capitalizes the discounted value of all future profits or rents that can be derived from the land. The advantage of the hedonic approach is that it relies on the cross-sectional variation to identify the implicit choices of landowners regarding the allocation of their land among competing uses instead of directly modeling their decision. Further,planter pots drainage the hedonic function also allows one to calculate the direct impact on each farmer, county or state, in contrast to the highly aggregated structural CGE models. This is the approach we adopt, though with a number of innovations indicated below and explained in detail in succeeding sections. In this paper we resolve some of the differences in previous studies by estimating a hedonic equation for farmland value east of the 100th meridian, the boundary of the region in the United States where farming is possible without irrigation. The main contributions of the paper are: First, we incorporate climate differently than previous studies, by using transformations of the climatic variables suggested by the agronomic literature. The relationship between climatic variables and plant growth is highly nonlinear and our approach yields results that are consistent with the agronomic evidence. Second, we develop a new data set that integrates the spatial distribution of soil and climatic variables within a county with the help of a Landsat satellite scan of the contiguous United States. Third, we allow the error terms to be spatially correlated to obtain a more efficient estimator and correct t-values . Fourth, we present several sensitivity checks, and show that our results are robust to both different specifications and census years. We show that results remain similarly unchanged when we include state fixed effects to control for the influence of state-specific factors unrelated to climate, such as property taxes and crop subsidies. Finally, we evaluate potential impacts of warming using new climate projections from the most recent runs of two of the major global climate models. The paper is organized as follows. Section 2 outlines a model of farmland value with attention to issues raised by irrigation. Section 3 addresses spatial issues that arise in the definition and measurement of climatic and soil variables and in the correlation of error terms.

Section 4 presents our empirical results, including tests for spatial correlation and estimates of the hedonic regression coefficients and discusses a variety of tests of robustness of the results. Section 5 uses the results to generate estimates of regionally differentiated impacts of climate change on agriculture. Section 6 summarizes our conclusions. In this framework, climate variables play two different roles. Temperature is an exogenous shift variable in the production function; increases in temperature increase the demand for water as an input and they can raise or lower yield, depending on the size of the increase.Precipitation has a different role in irrigated areas than in dryland areas. In dryland areas, the water supply for crops comes from precipitation falling on the field before and during the growing season; in this case, the water supply is fixed by nature in any given year, and it comes with a price of zero. In irrigated areas, by contrast, the water supply is man-made, using local groundwater or surface water imported from somewhere else, it comes at a cost, and the quantity is endogenously determined. In terms of location, since the time of John Wesley Powell it has been common to take the 100th meridian as a rough approximation of the rainfall line in the US. To the east, rainfall generally exceeds 20 inches per year while, to the west, rainfall is generally less than 20 inches per year. Since virtually all traditional US crops require at least 20 inches of water to grow, the 100th meridian marks the boundary of the arid West, where farming is generally possible only with use of irrigation.3 Thus the 17 western states account for about 88% of the 150 million acre feet of irrigation water used annually in the U.S. The economic implications of the distinction between dryland and irrigated farming are discussed in detail by Cline , Darwin , and Schlenker et al. , and will be summarized briefly here. In addition to the fact that precipitation does not measure water supply in the arid West, the other distinctive feature is that, in irrigated areas, future changes in water costs, unlike other input costs, are not likely to be capitalized in future land prices in the same way as past cost changes were capitalized in past land values. Many of the major surface water supply projects in the western United States were developed by the US Bureau of Reclamation or the Army Corps of Engineers and involved a substantial subsidy to farmers. Depending on the age of the project, there is substantial variation in federal irrigation charges across different projects, and these are clearly capitalized into farmland values. Failure to account for subsidies could bias other regression coefficients, especially climatic coefficients that in turn are correlated with the access to irrigation. Aside from the federal projects, the remainder of the irrigation supply in the western states comes from groundwater or from non-federal surface water storage projects.Nevertheless, in the case of irrigation with non-federal surface water it still would be misleading to predict the economic cost of a change in precipitation on the basis of a hedonic regression of current farmland values.

Climate change also has an impact on seasonal changes and timing of precipitation

San Diego’s landscape has historical and cultural importance, with more than 18 federally recognized tribes which is more Indian reservations than any other county in the United States . The combination of these natural open and agricultural lands, pristine coastal areas, diverse urban neighborhoods, and rich cultural history makes San Diego a vibrant and unique region that supports a variety of human communities and industries.Agricultural rangelands and croplands are an important feature within San Diego’s landscape, constituting 5.11% of the county’s total land with more than 250,000 acres and 5,000 farmers . These working lands are deeply rooted in the county’s landscape, holding historic, economic, environmental, and social significance while providing a multitude of local benefits. Not only are these working lands important to the county for providing the public with local products and counteracting urban growth, they have significant economic value. Ranked 12th largest in the nation, San Diego agriculture has an estimated $2.88 billion annual value to the economy . The region’s agriculture encompasses rangeland, pastureland, and cropland, used for growing annual, perennial, nursery, and field crops . Top crops include nursery products and crops, avocados, citrus, and miscellaneous vegetables . While the relatively moderate Mediterranean climate, in addition to a range of micro-climates, makes San Diego an ideal place to grow agricultural crops and livestock products , there are many challenges associated with farming in the region. San Diego’s current farmers face constraints on water-use efficiency and water availability that limits crop selection and efforts efforts to maximize production while also making a profit. From high irrigation demand,blueberry plant container increasing water costs and land prices, to pervasive pest and plant diseases, San Diego farmers have no choice but to utilize innovative farming techniques and choose smart crop choices .

Due to historic development patterns in San Diego, agriculture is often embedded within urban areas, with more small farms than any other county in the nation. Because of the average size of farms, the agricultural sector is spatially scattered throughout the unincorporated county, which can be difficult for identifying and monitoring existing agricultural land and practices. Nonetheless, San Diego’s agricultural production remains more valuable than many other urbanized areas of California, including San Francisco, Orange County, and Los Angeles combined . San Diego’s agricultural landscape is composed of diverse lands, with varying terrain, vegetation, and agricultural use. These lands provide valuable and beneficial services for the region’s food supply and ecosystems, including creation of wildlife, habitat, food for people and pollinators, and water filtration .At a latitude of approximately 32 degrees North, San Diego is situated in the heart of the subtropical climate zone. The region encompasses a unique landscape, positioned between the coastal zone of the Pacific Ocean to the west and the foothills, interior mountains, valleys, and deserts to the east. Like most areas in California, the region is known for its Mediterranean climate in which it experiences hot, dry summers, and mild winters . San Diego’s climate is characterized seasonally by latitudinal climate influences that cause this subtropical dryness in the summer and midlatitude storm-tracks in a concentrated wet season from October through April . Additionally, coastal low clouds and fog are a defining characteristic of San Diego’s climate. CLCF typically persist throughout early summer months, helping moderate heating, buffer dryness and solar insolation, while also providing cooling and water for the region’s coastal ecosystems . The combination of complex topography, coastal effects, and wide altitudinal ranges coupled with subtropical and midlatitude influences results in a range of diverse micro-climates throughout the region . In addition to impacting temperatures and humidity on the coast and further inland, the combination of these factors produce variability in monthly precipitation during the winter months . With annual precipitation totals varying from as little as 50% to greater than 200% of long-term averages, California experiences the largest yearly variations in precipitation compared to any other region in the U.S .

In particular, the year-to-year variability in southern California is higher than anywhere else in the U.S . The average annual precipitation for San Diego is 10.34 inches , however, historical averages reaching as low as 3.3 inches in 2002 and as high as 22.60 inches in 2005 highlight the region’s large inter-annual variability. Variability in precipitation is primarily tied to the number of extreme precipitation events, known as Atmospheric Rivers . ARs contribute to 68% of extreme-rainfall accumulations in southern California . Figure 4 illustrates the correlation between the number of these top 5% of rainy days and precipitation variability. Given that the occurrence of a few AR events each year dictate floods, droughts , and water availability , understanding these extreme events are important for regional weather forecasting, infrastructure planning, and resource management. The San Diego County Water Authority has served as the wholesale supplier for San Diego since its creation in 1944, working to secure reliable water supply for the region. SDCWA’s water supply sources have changed throughout San Diego’s unique historical periods. Despite these changes, SDCWA has consistently relied on imported water in some capacity . Currently, San Diego County imports around 80% of its water supply, using both local and imported sources . In the past, San Diego relied heavily on a single supplier of water, the Metropolitan Water District of Southern California , which includes water from Northern California and the Colorado Basin. Since the enactment of the Colorado River Compact in 1922, allowing for the diversion of water from the river to surrounding states, Colorado has been a major supplier for San Diego . In 1991, the MWD constituted 95% of San Diego’s water supply . In the last two decades, after an extensive drought that caused MWD to reduce water delivery to San Diego, SDCWA has developed several strategies and long-term plans to diversify the region’s water supply portfolio. These strategies aim to improve the region’s water infrastructure, promote water-use efficiency, and ultimately secure reliability of supply . In 2017, supply from MWD had significantly declined to 40%, allowing for inclusion of other sources. Agreements made with the Imperial Irrigation District, and the Coachella and All-American canals, which source water from the Colorado Basin, contributes another 40% of imported water to San Diego’s current supply portfolio. Local sources contribute the remainder of supply, including groundwater, recycled water, and desalination . Agriculture is one of the many sectors that is greatly dependent on these water resources. With water pricing escalating since the early 1990’s, water costs have been the primary water concern for San Diego farmers .

As drought conditions increasingly threaten the region’s imported water sources, farmers have shifted their focus towards water availability as well . While SDCWA has worked to ensure reliable and diversified water sources over the last few decades, new water sources have proven to be expensive . In the last 12 years, the price of water has tripled, while the revenue from farm products are generally consistent, creating challenges for farmers across the region. Water alone constitutes the largest monthly expense for many farmers . Thus, farmers are eager to adopt strategies that maximize water-use efficiency, minimize use and overall costs, and increase financial returns. For farmers who choose to participate in SDCWA’s special agricultural water pricing, water charges are priced at discounted rates. Nonetheless, costs per acre foot remain high, and much of the sector, specifically nursery, flower, fruit, and livestock farmers, do not participate . Not all of San Diego receives the imported water supplied by MWD and geographically,30 plant pot the majority of the unincorporated area is reliant on groundwater-dependent districts or private wells that are managed separately from SDCWA . Thus, these areas are completely reliant on groundwater resources and are impacted by its availability. The agricultural sector also relies on groundwater resources, and is considered one of the “large quantity” groundwater users . These groundwater resources are often limited due to unfavorable geology, resulting in aquifers with limited groundwater in storage volume and/or groundwater recharge. Several areas throughout the county that are groundwater-dependent, specifically the unincorporated county, face groundwater hydrology issues. Given that agricultural users are not regulated or metered for water quantity, these large quantity users can create localized groundwater problems throughout the groundwater dependent areas . It is clear that water resources, availability, and supply are major focuses for the county, especially the agricultural sector. With the need to limit water use to allow for profits, water concerns continue to be a driving force for the conservation efforts of San Diego’s farming community. It is projected that over the next several decades, California will continue to experience several changes associated with climate change, including sea level rise, precipitation patterns, and temperatures. Amid historic coastline and mountains, San Diego region encompasses many diverse climate zones. In turn, the region will likely experience a myriad of changes with dynamic, complex, and compounded effects. As a result, the county will face several challenges that could ultimately threaten the natural and human landscapes that it supports. While the region’s diverse ecological systems, industries and communities have adapted to San Diego’s variable and seasonal climate, climate change could exacerbate these conditions and ultimately threaten the survival of these valuable systems . As one of the most “climate-challenged” regions in North America, it is critical that the county understand these regional variations in climate impacts and vulnerability .

In the region, climate change will significantly increase yearly average temperature over the next several decades, with projections ranging from 5-10° Fahrenheit depending on the Representative Concentration Pathway greenhouse gas concentration and region . San Diego and neighboring areas will face varying changes in the average hottest day per year, daily maximum temperature and daily minimum temperature because of the region’s diverse topography and distinct micro-climates. Under RCP 8.5, representing a high concentration scenario, the average hottest day per year will increase from the historic range of 90-100° F to 100-110° F in coastal zones, and from 105-115° F to 110-125° F in desert regions . Temperature extremes are projected to increase, with climate warming increasing duration, frequency, and intensity of heat waves compared to historic climate . The probability of heat waves varies regionally, with some locations expected to have a greater probability of increase in the number of extremes, and in either daytime or nighttime heat waves. Extreme temperature events and increasing Tmax will further intensify the impacts of drought . Although it is projected that there will be fewer total wet days and a decrease in the number of ARs globally, these wet events will likely increase in width and length by 25%, in addition to intensity . With a Mediterranean climate that is uniquely balanced between both mid-latitude storms and expanding subtropical zones, projections for California’s precipitation regime show more uncertainty and variability compared to most other Mediterranean climates around the world. While models consistently project future drying over Mediteranean climates globally, projections for California diverge from these trends, becoming wetter in winter aggregate and experiencing increases in mean precipitation . As a result, the region will likely experience wetter winters yet longer, dryer warm seasons, contributing to increased year-to-year variability. With intensified extreme precipitation events, climate models indicate that the variable character of Southern California’s precipitation will continue to increase .It is projected that precipitation will increase during the region’s concentrated wet winter season, while decreasing in both autumn and spring . Warmer temperatures are causing winter precipitation to fall in the form of rain rather than snow, meaning that the snow pack that acts as a natural reservoir for the state’s water supply will be diminished . As less precipitation is stored in these snow pack reservoirs, compounded with warming temperatures, the state is experiencing earlier springtime snow melt . These projected changes in snow pack, precipitation and springtime snow melt will continue to challenge many regions of California, defining the state’s current and future water resources . Although local snow pack is not significant, loss of snow pack in the state overall will negatively impact the imported water supplies that San Diego relies upon.Coastal low clouds and fog that migrate along the West Coast fluctuate on annual and decadal scales, as a response to a combination of naturally occurring climate and weather patterns .

Are Plastic Pots Bad For Plants

Plastic pots are commonly used for gardening due to their affordability, lightweight nature, and durability. However, there are some considerations to keep in mind when using plastic blueberry pots for plants:

Advantages of Plastic Pots:

Durability: Plastic pots are long-lasting and can withstand outdoor conditions without deteriorating as quickly as some other materials.
Lightweight: Plastic pots are lightweight, making them easy to move around, especially for larger plants.
Cost-Effective: Plastic pots are generally more affordable than pots made from other materials like ceramic or terracotta.
Moisture Retention: Plastic pots tend to retain moisture better than some other materials, which can be beneficial for plants that prefer consistent moisture levels.
Variety: Plastic pots come in a wide range of sizes, shapes, and colors, allowing you to choose containers that suit your aesthetic preferences and the needs of your plants.

Considerations:

Aeration: Plastic pots may not provide as much breathability for plant roots compared to porous materials like terracotta. This can potentially lead to waterlogged soil and root rot if proper drainage is not maintained.
Heat Absorption: Dark-colored plastic pots can absorb and retain heat, which might raise the temperature of the root zone and impact plant health, especially in hot climates.
Degradation: Over time, plastic pots can become brittle and fade due to exposure to sunlight, which may reduce their overall lifespan and appearance.
Root Circulation: Some plastic pots have smooth sides that can lead to root circling, where roots grow in circles around the interior of the pot. This can negatively affect plant health in the long term.
Environmental Impact: Many plastic pots are made from petroleum-based plastics, which have environmental implications due to their production, use, and disposal.

Tips for Using Plastic Pots Effectively:

Choose Proper Drainage: Ensure that your plastic pots have adequate drainage holes to prevent waterlogging and root rot. Elevating pots slightly can also improve drainage.
Monitor Root Health: Regularly check the roots of your plants for signs of circling or compacted growth. If necessary, repot plants to prevent root-bound issues.
Consider Light Color: If you’re concerned about heat absorption, choose lighter-colored plastic pots that reflect more sunlight and heat.
Use Saucers: Place plastic pots on saucers to catch excess water and prevent staining of surfaces. This can also help maintain proper moisture levels.
Recycling: Look for pots made from recycled plastic or consider recycling your old pots to reduce their environmental impact.

In summary, best indoor plant pots can be suitable for many plants, especially when proper care is taken to address potential issues like drainage and aeration. However, it’s also important to consider the needs of your plants, your local climate, and the environmental impact of using plastic materials. If you’re concerned about these factors, you might explore alternative pot materials like terracotta, fabric, or biodegradable options.

Several mechanisms can cause the formation of a water layer

A ‘water layer’ in the field of ISE research refers to a small water layer that can form between the conductor and transducer. This water layer then acts as an unintentional electrolyte reservoir that re-equilibrates with any change in the bulk sample composition.If the ISM and transducer layer do not have good contact with the subsequent layers and do not form a hydrophobic seal, then it is possible for the bulk solution to ‘fill in’ the space by capillary force, not unlike water soaking into a napkin or paper towel. However, if there is a good seal in different layers, it is still possible for a water layer to form. For example, if the micro-structure of the ISM contains ‘pinholes’ , water can likewise transport through these channels to the layers below. Pinholes can be avoided by careful deposition techniques or by making thicker ISM layers. For the latter, the likelihood of forming a pinhole penetrating through the entire membrane is inversely proportional to the membrane thickness. Finally, even if there is a hydrophobic seal and there are no pinholes, water will still diffuse through the membrane to some degree, as the diffusion coefficient of a typical PVC membrane is on the order of 10−8 cm2/s. This is why PVC and other hydrophobic polymers are frequently chosen as the polymer matrix – their high level of hydrophobicity and small diffusion coefficients make it so the water diffusion rate through the ISM is negligible. A simple test to determine if a water layer is forming within an ISE was designed by Fibbioli et al.and is now widely used within the field of polymeric ISE research.

As it has come to be known,draining pot the’ water layer test’ is a relatively simple three-part potentiometric measurement. First, the ISE is conditioned in a concentrated solution of its primary analyte. Then, the electrodes are moved to a concentrated solution of a known interfering analyte. Finally, the electrodes are placed back in the concentrated solution of the primary analyte. The electrode potential is continuously recorded against a commercial Ag/AgCl RE following each exposure to the different solutions. The duration that the electrodes need to be soaked in each solution depends on the thickness of the membranes and the ISE response. Each exposure lasts several hours, and some experiments lasting up to 45 hours have been reported. A schematic describing the water layer test for a nitrate ISE is shown in Figure 4.14. Figure 4.15 shows the water layer test performed on the nitrate ISE. In this water layer test, 100 mM NaNO3 was used as the primary solution, and 100 mM NaCl was the interfering solution. First, the ISE was conditioned in 100 mM NaNO3 until it was stable. The final hour of stable output in NaNO3 is shown, followed by two hours in the interfering solution, and returning to NaNO3 for 24 hours. The potential shows some drift during both the NaCl step and the NaNO3 return, which could indicate the presence of a water layer on the electrode’s surface, which is not unexpected for this type of coated-wire electrode. However, the electrode’s stability is on par with values reported in the literature, which involved specific modifications for stability. The difference between the potential immediately before and the potential immediately after the NaCl step is 15 mV, the same as found by Chen et. al. for electrodes using gold nanoparticles and Polypyrrole to improve stability. Another technique for investigating the stability of an ISE is current-reversal chronopotentiometry. Recall that in Equation 4.10, potential drift is inversely proportional to the capacitance of the ISE.

Current-reversal chronopotentiometry is a technique that allows one to find the capacitance of an ISE. Current-reversal chronopotentiometry is a three-electrode electrode technique with the ISE as the working electrode , a commercial Ag/AgCl electrode as the RE, and a glassy carbon electrode as the counter electrode . The WE is polarized with a few nanoamps of current while the electrode potential is recorded. Rearranging Equation4.10 allows one to solve for the capacitance from the rate of potential change and the current input. After a short period of time, the current flow is reversed, and the bulk resistance of the electrode can be calculated from the ohmic drop when the current is reversed by rearrangement of Equation 4.9. A nitrate ISEs was configured into the three-electrode system described above and submerged in 100 mM NaNO3. A +1 nA current was applied for 60s, at which point the current was reversed to -1 nA for another 60s. The potential is plotted over time in Figure 4.16. EIS is an electrochemical technique that provides in-depth information about the dielectric properties of solid-state ISE sensors. EIS can also identify water layers, pockets of water in membrane pores, and pinholes. Finally, EIS characterizes the contact resistance of the boundaries between layers, which should be minimized to ensure a hydrophobic seal and reduce the ISE impedance. The nitrate ISEs were configured in a three-electrode system, with the ISE as the WE, a commercial Ag/AgCl electrode as the RE, and a glassy carbon electrode as the CE. The three electrodes were immersed in 100 mM NaNO3 solution and the impedance spectra were recorded in the frequency range of 0.5 Hz – 200 kHz. The Bode plot is shown in Figure 4.17A, and the Nyquist plot is shown in Figure 4.17B. The electrode demonstrated a bulk impedance of 1.72 MΩ. Higher bulk resistance of ISEs with PVC and DBF-based membranes has been previously reported, which could be accounted for by membrane thickness and the lack of a transducer layer in our device.Precision agriculture offers a pathway to increase crop yield while reducing water consumption, carbon footprint, and chemicals leaching into groundwater.

Precision agriculture is the practice of collecting spatial and temporal data in an agricultural field to match the inputs to the site-specific conditions. While industrial agriculture seeks to maximize crop yield, there is also the consideration of maintaining a healthy ecosystem. Fortunately, these are not competing interests; Numerous case studies have demonstrated that adopting precision agriculture techniques increases crop yield while lessening detrimental environmental effects. Consider first the use of irrigation in agriculture, which accounts for approximately 36.7% of the freshwater consumption in the U.S., 65% in China, and77% in New Zealand. Part of why so much water is used in agriculture is, quite simply, because crops need a lot of water to grow. For example, high-production maize crops require 600,000 gallons of water per acre per season – that’s an Olympic swimming pool’s worth of fresh water per acre! Adopting precision agriculture practices – such as variable-rate irrigation – have proven to reduce water consumption by 26.3% . Meanwhile, fixing nitrogen from the air to produce fertilizers is an extraordinarily energy-intensive process and accounts for nearly 2% of the U.S.’s annual CO2 emissions. Crops recover only 30-50% of nitrogen in fertilizers, which means that over half of the nitrogen becomes a potential source of environmental pollution, such as groundwater contamination, eutrophication, acid rain, ammonia redeposition, and greenhouse gases. Fortunately, precision agriculture practices have demonstrated an increase in nitrogen use efficiency, thereby reducing both the production volume of fertilizer as well as the amount that is polluted into the environment. We began this exploration from the ground-up. First, we investigated how many sensors are needed to inform a precision agriculture system. The results of that work informed the design of nitrate sensor nodes to fulfill those specifications,round plastic planters and lab-scale versions of those nodes were fabricated and tested in greenhouse experiments. After these WiFi-enabled nitrate sensor nodes were validated, we replaced the components of the nitrate sensor node with naturally-degradable alternatives to realize a no-maintenance version of the sensor node. The fabrication methods were scalable and low cost, while the sensors were comparable to their non-degradable twins. Such sensors could be widely distributed throughout a landscape to map nitrate movement through the watershed, inform the efficient application of fertilizer, or alert residents to elevated nitrate levels in drinking water.Accurate soil data is crucial information for precision agriculture. In particular, the moisture content and the concentration of various chemical analytes in soil have a significant influence on crop health and yield.

These properties vary considerably over short distances, which begs the question: What spatial density does soil need to be sampled to capture soil variability? Half of the spatial range, referred to hereafter as the ‘half-variogram range’, can be used as a “rule-of-thumb” to account for the spatial dependency of agricultural measurements.Similar to how an agricultural field can be defined in the real world as a geographic area at a location, a digital representation – or ’simulation’ – of an agricultural field can be defined as many discrete pixels, where each pixel’s position corresponds to a geographic coordinate and its size to an area. Here, we briefly discuss three methods of expressing an agricultural field in a digital format. For agricultural fields that a simple geometric shape can approximate – such as a rectangular farm or a central-pivot farm – expressing the farm digitally is trivial. For a rectangular-shaped field, we discretize the space into a grid of uniform pixels with dimensions proportional to the length and width of the physical domain. For a central-pivot field, we bound the field in a square grid of uniform pixels, loop through each pixel in the grid, and add the pixel to a list if that pixel’s coordinates are equal to or less than the field’s radius. This technique is demonstrated in Figure 5.2A for a rectangular-shaped field and in Figure 5.2B for a central-pivot field. When the boundaries of the agricultural field are not regularly shaped, we define the field by a list of consecutive coordinate points that, when piece wise connected by polynomial curves, form an enclosed shape. Here, we adopt a simple ray tracing algorithm to determine whether or not a pixel is inside or outside of this boundary. Given an enclosed boundary and a point in space, if one were to draw an infinite vector in any direction originating from that point, it will intersect the boundary an odd-numbered amount of times if-and-only-if the point is within the enclosed space, which is shown in Figure 5.2C. This holds for all points in space except for points on the boundary, which must be determined explicitly. In this way, we use the coordinates of each pixel as a point to determine if a pixel is inside the boundary and append it to a list. Finally, satellite or drone visible-spectra images of agricultural land are already stored in a digital, pixelized format. Such images and datasets are widely available from Google Earth, NASA Earth Observatory, or the USDA cropland data layer. Computer vision techniques can differentiate the arable land on a field from obstructions and store those pixels in a list. This process is visualized in Figure 5.2D. In all cases, it is essential to note the physical dimensions that a single pixel represents. It should also be noted that because each method requires discretization of the field, the results are approximations whose accuracy increases proportionally to the number of pixels used.The optimal layout of sensors in an agricultural field is achieved when, using the fewest number of sensors possible, all points in the field are statistically represented by the data collected by sensors in that field. For a given sensor, the data collected from that sensor is statistically significant for all points within a radial distance equal to the half-variogram range of that sensor. Thus, if we consider an agricultural field a two-dimensional collection of pixels, we can model sensors as circles with a radius equal to the half-variogram range. Using this definition for placement, our problem is similar to the circle packing problem. Circle packing is a well-researched area in mathematics that has many practical applications. Object packing aims to fit as many of some objects within a domain as possible without any overlap. There are several algorithms that aim to optimize object packing, such as random sequential addition, the Metropolis algorithm, and various particle growth schemes. The limit of packing efficiency for equal-size circles in two dimensions is about 91% for a hexagonal grid.

Most economic models make simple profit maximization assumptions

Management data tend to be sparsely available and representing continuity of plant populations is challenging. Advancing our ability to understand how grasslands are managed – to understand, for example, what species are planted, what inputs are provided, what grazing management is applied – is centrally important for improving our ability to model pasture and range land systems. Planted pastures and native grazing lands both contain a variety of species, some of which are more palatable, nutritious, grazing-resistant, or fire-resilient than others. A more open, data-rich environment could facilitate evaluation of a variety of approaches for representing long-term dynamics, which could address several important grassland management and assessment issues. Managing grass swards to maintain desirable plants is a primary goal of grassland management, but one for which modeling tools have offered limited assistance. Models that represent vegetation dynamics are also desirable for understanding longer-term changes in species that can impact productive capacity, sensitivity to degradation, and carbon dynamics . Year-to-year variability is a key component for understanding potential utility and risk of relying on grassland forage resources. Next generation models that enhance our ability to forecast this risk would mark a substantial and meaningful advance. There is a need for better links between the agricultural modeling communities and ecological researchers studying long-term vegetation dynamics. The primary use of forage resources is for grazing animals, yet most grassland models are only loosely coupled with grazers . Better integration through grazing effects on grasslands, grazer distributions across landscapes,plastic pots plants forage demand/consumption, livestock/wildlife movement, etc., would enhance the ability of models to contribute to important emerging issues.

For example, holistic grazing management, in which several aspects of management vary in response to a variety of different cues from the land and expectations about future conditions, can be impossible to evaluate with current modeling frameworks. A system that integrated user demand into the model development process could lead to implementation of new data-management feedback loops within models. Such interactions between users and producers of information could direct data collection to facilitate model use. Models that better represent grazer-grassland interaction are also crucial for understanding how efficiently livestock use forage resources, what is necessary to sustain wildlife populations, and how much grassland output might be available for other uses .The Intergovernmental Panel on Climate Change has reviewed the existing evidence for how climate change may affect weeds, pests, and diseases . One issue with this evidence base is that there is a clear publication bias towards reports of increased threats – people often do not bother to write up no-effect results. There is a general recognition that we need good models to help tease out different effects that changing weather will have simultaneously on both crops and the organisms that compete with or attack them. There has already been some work applying crop physiology-type models to weeds, and developing more mechanistic models of the effect of temperature on insect pests. There is an opportunity and need for more integrated models that include interactions between organisms, for example between weeds and crops, and between pests and the predators and parasites that attack them. A variety of different approaches are possible, and there is a need for an AGMIP-type approach to help the community decide how best to move forward.Highly contagious diseases of livestock present a major threat to agriculture, both in the developed and developing worlds.

Diseases may be chronic in livestock populations, emerge from wildlife reservoirs, or possibly be introduced deliberately by man as an act of bio-terrorism. Models are required to help understand how a disease will spread, and to help policymakers design optimal interventions. These models must encompass not only the epidemiology of the disease but also how it is affected by agricultural practices and in particular the movement of livestock by farmers. There have been significant recent advances in this area, often building on work on human diseases. For example, it is now possible to take livestock movement data and use it to parameterize an epidemiological model . There are the beginnings of a model comparison movement in human epidemiology; livestock disease epidemiology would also benefit from this approach.There is intense current research activity into novel genetic methods of insect control. Most of this work is currently directed at the insect vectors of human diseases such as malaria, though the same methodology can be applied to insect pests of crops and of course the vectors of livestock diseases. The greatest advantage of these approaches is that they involve self-sustaining interventions that spread naturally through a pest population, although because they are nearly all classified as genetically modified, the regulatory issues surrounding them are complex. Cutting-edge modeling work in this field involves joint population and genetic dynamic models, many of which are explicitly spatial. This topic is likely to be one of the most important and exciting areas of modeling as applied to agriculture over the next few decades.Integrated agricultural technologies, defined as the integration of improved genetics, agronomic input, information technology, sensors, and intelligent machinery, will play a pivotal role in agriculture in the years to come. These innovations will be driven by economic forces, by the need to produce more food with limited land and water for the increasing population, and at the same time by the push to save resources to reduce the environmental impact associated with food production. While these changes are occurring now in the commercial scale industrialized agricultures of the world, many of these technologies have the capability to be adapted to conditions in other parts of the world.

The cell phone now allows farmers in rural areas almost everywhere in the world to have low-cost information about prices, for example. Similarly, it is likely that unmanned aerial vehicles will rapidly be adapted to conditions around the world and used to carry out activities such as monitoring crop growth and pest occurrence, and improve management decisions. In large-scale, capital-intensive agricultural systems, these technologies are rapidly leading to the automation of many production activities, particularly machinery operation and decisions about input application rates. The automation of agriculture began in the mid-nineties, resulting in large amounts of data available to farmers and agribusiness companies. Farm machinery are now often equipped with high precision global positioning system controllers, which allow all activity on the farm to be recorded, geo-referenced, and stored on remote computers: “in the cloud.” All modern tractors collect data on a continuous basis and are equipped with wireless connectivity for data transmission. Harvesters record the yield at a particular location, planters can vary the plant spacing or type of seed by location, and sprayers can adjust quantity and type of fertilizer, fungicide or pesticide by location; all to a granularity of just a few square meters. Yield monitoring can now be linked to unmanned aerial vehicle imagery to produce a prescription map for the farmer to implement. These private data could also provide tremendous benefit to the researcher community, should access be increased. Producers in some regions of the world now have historical crop yield data for their fields at very high resolution. Combined with advanced satellite-based imagery, high-resolution spectral and thermal data obtained from UAVs,plastic nursery pots and weather forecasts, growers have most of the critical inputs required to convert this “big data” into an actionable management plan with equipment that can vary fertilizer and other inputs spatially within a field. Despite these rapid advances in the sophistication and automation of farm equipment, a vital piece of the equation is still lacking: the analysis of the vast amount of newly available data in order to provide the farmer with a map of what action to take where and when. Most variable rate application is currently managed by farmers, using rule-of-thumb and empirical approaches, and not by using a systems approach that accounts for the interaction of soil, crop, management, and weather. Thus much of the power of automation remains unexploited. In order to realize the full potential of more sophisticated equipment, new modeling systems for precision agriculture are needed. These systems could be based on comprehensive predictive crop yield models that combine publicly available data, such as soil type, weather, and prices, along with location-specific data from farmers’ yield maps of their fields, to provide a prescriptive crop management plan at high spatial resolution, as in Fig. 2. This type of system could deliver automated crop simulations, crop management strategy recommendations, process-based variable rate prescriptions, risk assessments, continual in season simulations, integration of in-season crop scouting UAVs flight information, pest management prescriptions and accurate harvest recommendations via simple-to-use apps, websites, or smart phones. In addition to the farm-to-landscape scale analysis represented in Fig. 2, there will be a growing demand for agricultural systems models to simulate and integrate the different components of the agricultural value chain, to meet both policy requirements and corporate sustainability goals . Genetics, agronomic management , weather, soil, information technology and machinery will need to be linked in a system approach to address these informational needs. This is a new frontier for agricultural system modeling that would extend to the broader food system and raise additional data and analytical challenges.

As illustrated in Fig. 2 and discussed in the previous section, various management and production data are becoming available through mobile technologies . An example of this analytical capability is the AgBizLogic™ software developed by several university extension programs, which allows managers to calculate short-term profitability and rates of return on long-term investments . Similar proprietary software tools are being developed and used. These analytical tools could be linked with modules that track or predict environmental outcomes such as soil erosion and net greenhouse gas emissions . Low-bandwidth versions of these tools need to be developed for use in areas where mobile phone technology is a limiting factor. Analytical tools need to be adapted to fit small-holder systems as indicated by the NextGen Use Cases. The flood of data on physical land-use, water availability and use, and yields coming from mobile devices and remote sensing systems suggest that both the biophysical and behavioral aspects of farm production at specific locations can be estimated by sequential learning processes. The use of advances in computational methods such as machine learning and remote sensing data is illustrated by analysis of the impact of the 2009 and 2014 droughts on California agriculture, which demonstrated the advantages of better data .To facilitate the use of models for various locations and systems, and to link to crop and livestock system simulation models, economic models need to be incorporated into modules with standardized inputs and outputs. Various types of economic models are available in the literature, including farm-level optimization models, regional positive quadratic programming models, econometric land-use models, and regional impact assessment models . User needs should dictate which types of models should be used depending on informational needs. Methods and protocols are required to link regional economic models with market equilibrium models . Some progress has been made on this front but much more development is needed to address various aggregation and dis-aggregation issues . Generalization of behavioral assumptions and investigation of their effects on investment and policy analysis is also needed.There is a rich literature on risk modeling which could be incorporated. Recent advances in the expectations formation literature and the behavioral economics literature could be investigated for use in agricultural systems models.The application of different farm improvement methods has explicit winners but also unintended ‘casualties’ and perverse incentives. From a development standpoint, it is essential to understand these dynamics to ensure that appropriate policies are developed to maintain equal opportunities for all sectors of society. For example, in many cases, rich farmers are the ones who adopt technologies early. This factor could potentially disrupt power relationships in markets, thus affecting poorer farmers. In this case it is essential to design alternative options and safety nets for poorer farmers to prevent widening the gap and making them more vulnerable. New models should improve our understanding of these processes, as we move from single farm models to multi-farm and regional models. Methods utilizing population-based data are providing improved capability to represent distributional impacts and vulnerability .Current agricultural system models typically operate at the point/ field scales with an emphasis on vertical fluxes of energy, water, C, N and nutrients between the atmosphere, plant and soil root zone continuum.

Contributions to transportation technologies evolved throughout the past 150 years

The list includes development of large-grain combines, crawler tractors, the centrifugal irrigation pump, mechanical fruit and nut harvesting systems, aerial application systems, etc. Unlike much of U.S. agriculture, which is dependent on machinery and equipment lines of large national manufacturers, California producers rely on mechanical technologies from several sources—from large machinery and equipment lines for general purpose tractors and combines, from foreign manufacturers for specialized, precision equipment for special production uses , and from local inventor-manufacturers who design and/or take over the manufacture of equipment that was first developed on farms and ranches for very specific needs. The industry will maintain its reliance on productivity-improving and/ or cost-reducing mechanical technologies for continued economic success.An open border and a global economy bring the possibility of new pests that adversely affect the economic productivity of California agriculture. It is increasingly difficult to provide both effective monitoring of local production areas and thorough inspection of incoming plant and animal materials for potential threats to the state’s agriculture. Some examples: the Mediterranean fruit fly threatened the state’s fruit industry in the 1980s; foot and mouth disease, mad cow disease, and Newcastle’s disease are of constant concern to the livestock and poultry industries; African bees could imperil the apiculture industry; the spread of Pierce’s disease by the glassy-winged sharpshooter has already decimated southern grape-growing regions and has the potential to cause great economic damage if introduced into other major grape-growing regions; the spread of phylloxera required removal of grapevines and replanting on resistant root stock, etc. Adaptive pest management, required to maintain the economic viability of agricultural production through variety selection,square plastic pot integrated pest-management programs, eradication programs, cultural practices, and the like, will continue to be critically important to 21st Century agriculture.

Technology will be important in delivering quality products in larger quantities to diverse markets worldwide. Drivers 8 and 9 are listed separately in our table, but here they are discussed together as they are often of joint importance to market delivery of high quality products to both domestic and export buyers. In a demand-driven system, products must be quickly delivered to consumers in an assured form and quality. The produce of California’s farms and ranches has always greatly depended on national and international markets. Early on, international markets, which could be reached by sea, were more accessible than were interior domestic markets. That changed with completion of the transcontinental railroad in the late 19th Century. Ice cooling opened domestic markets for perishables in the early 20th Century. Post-WWII construction of the interstate highway system triggered another shift in the mode of transport—from rail to refrigerated trucks—for servicing domestic and nearby Canadian and Mexican markets. More recent innovations—refrigerated container shipments and air freight—permitted development of overseas export markets. Each major innovation led to structural changes in product mixes from extensive to increasingly intensive types of agricultural production. Efficient, timely transportation will continue to be of paramount importance to the economic viability of California agriculture. Early expansions of commercial agriculture featured livestock products and nonperishable commodities —products that required minimal processing and, in a relative sense, did not require extraordinary storage skills to maintain market acceptability. Subsequent development of the fruit industry went through several major changes, first from dried fruit to development of markets for processed and frozen products and then to a major emphasis on fresh fruits. Simultaneously, the challenge also was to deliver products to markets located more distant from producing orchards and vineyards. Scientific understanding of the post harvest physiology of harvested crops grew to be of paramount importance in the 20th Century, leading to practices that include quick post harvest cooling and control of atmospheric conditions during packing, storage, and shipping.

Parallel shifts are noted for the vegetable industry, which has also moved to a predominantly fresh product form for domestic and foreign consumers. In summary, the import of improved transportation technologies impacted the industry earlier than did a focus on processing and storage. In contrast, contributions to improved or new processing and storage technologies have been of growing significance, especially during the post-WWII period, underpinning the transformation of California agriculture from a majority dependence on extensive field and livestock products to one dominated by more intensive production of fruits, nuts, and dairy products that move to worldwide markets.Financial problems in the last two decades of the 20th Century and the related wave of megamergers of regional banks into national banks have changed the lending environment. Agricultural firms no longer compete in segmented capital pools for agricultural-related loans. This has been a major structural change. Now, credit markets are mostly nationwide markets with little or no differentiation in the designated portions of loan portfolios dedicated to agricultural firms—farms and businesses. The result is that all firms compete in much larger markets, putting additional stress and uncertainty on many small- to medium-sized farms and agribusinesses. Smaller firms may be competitively disadvantaged unless they have an economically viable niche market for product or services or unless they have non-farm sources of income. The distribution of farms by size of farm has become increasingly bimodal as the industry has been exposed to the several financial challenges during the recent two decades. In California and the United States there are growing shares of small-sized farms of minor commercial significance and a relatively small number of large farms that produce the majority of agricultural production. In between there is a group of small-sized commercial farms with operators who are dependent on farm sales as the chief source of income. Our assessment continues to acknowledge the realities of a capital-intensive industry facing significant structural changes in product markets that generally favor larger over smaller producers in meeting the quantity and quality specifications of supply contracts. Some will require capital not only to expand production but also to integrate production with processing and marketing activities , involving themselves in production of a wider suite of products or in other production regions —all efforts to maximize returns on internal and external sources of capital.

Thus, for these firms, access to capital will continue to be important if they are to respond successfully to changing economic realities into the 21st Century. Our assessment also recognizes the increasing scrutiny of the creditworthiness of small- and medium-sized firms, which require higher levels of internal funding for loan security. While changes in capital markets are of limited concern to small farms that are characterized by residential, retirement, or part-time farming interests, financial stress will likely persist for medium-sized operations attempting to remain commercially viable. Viability is challenged by the low return on small levels of production and the difficulty in competing for production contracts favorable enough to attract adequate levels of external financing. Without a successful adjustment outcome, they will be destined to either exit the industry or, at best, experience even lower levels of returns on management and internal capital and/or be increasingly dependent on non-farm incomes.Labor availability and cost, always important to California growers and processors, will be influenced to greater degrees by global political and competitive conditions. The entry of waves of cheap labor pools from Asia and the Americas has been, over time, fostered both by legislated programs and illegal immigration. While past periods of uncertain labor availability and/or rising labor costs have fostered development of important labor-saving technologies, the magnitude of recent growth, as well as the intensification of agricultural production, has resulted in more than offsetting increases in labor requirements. Total hired-worker employment in agriculture grew from about 200,000 man-year equivalents in the early 1960s to nearly a quarter million by the mid-1990s. While the number of regular workers did not increase over the period,square plant pot seasonal employment did increase significantly, rising from 50 percent to 64 percent of average employment . Agriculture’s need for a cheap supply of relatively unskilled seasonal labor, as unattractive as this initial employment opportunity may be, has provided a common starting point for numerous immigrant groups who later move to more attractive jobs throughout the economy. At a time when California agriculture is nervously watching the production potentials of low-labor-cost competitors for U.S. and world market shares, two domestic policy issues loom on the horizon, casting much uncertainty about ample labor supplies. First, continued high recessionary unemployment may reduce prospects for legal, guest-worker types of federal programs. Second, tighter borders instituted as a part of elevated homeland security measures could reduce available supplies of low-cost labor to both agriculture and non-farm service employers. President Bush’s recently proposed immigration reform may reduce labor uncertainty if legislation follows to move a portion of the illegal immigrant workforce to legal, green-card status. Overall, drivers 10 and 11 are judged to be less positive for agriculture in the coming years. Both are critically important. They differ only in their effect on farms with different characteristics. Increased segmentation of financing favors farms with more favorable commercial opportunities; medium-sized farms will continue to be financially challenged. Labor availability issues concern firms of all sizes.Superior management capability and effective implementation are the hallmark of firms that achieve better economic performance even while constantly undergoing structural adjustment. Management expertise is one characteristic of firms surviving turbulent economic challenges. Successful California farmers and producers have accepted forces of change, including those often thrust upon them from external sources, as they seek to reduce per-unit costs of production as well as to react positively to production innovations and opportunities for new commodities and product forms.

Adaptive skills are a necessity, including an acceptance of inherent risks and uncertainties along with strategies for managing potential risks to the firm, whether it be a farm, a ranch, or an agribusiness that extends beyond the farm gate. Our evaluations of the three major historical epochs reflect the ever-increasing contribution of superior managerial skills to development of California agriculture. California farms and ranches, often more diverse in structure than is common elsewhere, are extremely demanding of managerial skills. The existence of multi-product, integrated firms requires higher levels of managerial expertise. Smaller firms also require superior management in order to compete. The premium for a range of superior management skills will continue to be valued in forthcoming responses and initiatives that will be key to success and survival in California agriculture.Marketing is obviously important to California farms and agribusinesses. Management and important institutional innovations contributed mightily to the growth and development of California’s agriculture, especially in the early 1900s. Among the important institutional innovations were an exemption from U.S. antitrust laws, permitting growers to act collectively to process and market their crops and to share information; bargaining through grower cooperatives ; and growers’ ability to act collectively to control various aspects of marketing their products by federal legislation and state legislation . These were especially important to the growth of specialty-crop production . As the state’s capacity to produce specialty crops expanded, several commodities quickly developed a dominant marketing cooperative that controlled a majority of the California market volume. Examples included Sunkist , Sunsweet , Sun-Maid , Almond Growers Exchange , Blue Anchor , Nulaid , Diamond Walnut , Calavo , California Canners and Growers, and Tri Valley Growers . Early emergence of marketing cooperatives especially fostered the growth and development of irrigated agricultural production featuring more perishable fruits and specialty crops, but several cooperatives also emerged for field crops, e.g., RGA and CalCot . Cooperatives gave growers the opportunity to achieve scale economies by integrating collectively to gain benefits of larger volume processing and marketing activities as well as to benefit from joint information sharing and bargaining activity . Government-organized federal and state agricultural marketing agreements also grew from inception in popularity and importance, recently accounting for 54 percent of California’s agricultural output, being most important for animal products, vegetables, and fruits and nuts and least important for field and nursery crops . Depending on the specific marketing order, producers are required by law to contribute toward financing mandated marketing programs, the most common being for quality control involving standardized grades and minimum-quality standards by inspection, generic advertising and promotion in domestic and foreign markets, and research. The contribution of both cooperatives and marketing orders has been increasingly challenged in the recent past, such that we must conclude that their importance has declined in the late 1900s and will likely continue to decline in the future .

Water then replaced labor as the dominant issue in California agriculture

Expansion of agricultural production caused groundwater overdrafts to resume in the 1940s. However, construction on the CVP was suspended during the war years , delaying the availability of new surface-water supplies to production areas with over drafted groundwater supplies. In 1948, California permanently took over as the largest agricultural state in the Union in terms of value of production .California emerged from the first half of the 20th Century as the leading state in the U.S. military/industrial complex. Its agriculture had weathered the Depression, had regained health during WWII, and was poised to expand as the CVP came online. At mid-century, the future must have been seen as a time of great promise for the state. The second half of the century, at least until the 1990s, met that promise. California’s population grew in the next 50 years from 10 to 35 million people. California gross domestic product generally grew faster than that of the United States, meaning per-capita California GDP exceeded the U.S. GDP in most years. In fact, by the end of the century, California was being touted as either the fifth or sixth largest economy in the world, exceeding Canada in both population and GDP and Italy in GDP. The growth was fueled by rapid expansion, first in the aerospace industry and then in electronics and computers. California led the nation in both fields. Also, military expenditures remained high through the 1980s. For example, in the 1960s California received 20 percent of all U.S. defense contracts . Of course, when defense cutbacks came in the 1990s, California suffered a disproportionately high share of defense reduction. Immigration slowed substantially,drainage gutter a severe recession struck the state in the early 1990s, and the state continued to suffer through a prolonged and severe drought.

A rapid recovery in the second half of the 1990s, fueled in part by the “dot com” boom, quickly collapsed into a recession in the first years of the 21st Century, bringing with it severe financial difficulties for the state. We now proceed with the last two vignettes in our epochal history. It goes without saying that it becomes more difficult to describe California agriculture in simple or brief terms. Still, despite the increased complexity, the need for brevity persists. Therefore, what follows in Epoch 7 and Epoch 8 are at best highlights and more likely are selective illustrative anecdotes.The decades of the 1950s and 1960s were boom periods in California. The population nearly doubled from a little more than ten million in 1950 to almost 20 million in 1970. The 1950s were particularly explosive; population increased by 5.1 million—a more than 50 percent increase within one decade. Incomes grew quickly as the Cold War spurred rapid economic growth, particularly in the new aircraft and electronics industries as well as in older line industries such as agriculture and motion pictures. Massive investments in infrastructure continued in water projects, highways, airports, ports, higher education, and urban development. Virtually all of the increase in population was in burgeoning urban areas on the south coast, particularly in the Los Angeles basin and the San Francisco Bay Area to the north. With rapidly expanding housing growth, mostly in sprawling single-home subdivisions, urbanization accelerated the takeover of agricultural land. In just 20 years, Los Angeles County went from producing the highest value of agricultural production in the state—and in the nation—to being out of the “top ten” California counties in 1970. Vast stretches of Orange and San Diego Counties, longtime major producers of citrus and subtropical fruits and vegetables, were developed quickly, beginning in the 1960s with the Irvine Ranch and continuing through the 1970s and 1980s.

In the north rapid urbanization quickly consumed much of Santa Clara County’s agriculture, pushing fresh- and dried-fruit production into the Sacramento and northern San Joaquin Valleys. The rapid relocation of production was able to occur, in part, because the state’s stock of irrigated land increased from less than five million acres in 1945 to more than seven million acres in 1970, peaking at around 8.5 million acres in the 1980s. Virtually all of the expansion came from publicly funded large-scale projects. Water in the Delta-Mendota Canal in 1953 signaled completion of the CVP, which “brought over a million additional acres of San Joaquin Valley land into production by the mid 1950s” . The SWP was nearing completion at the end of the 1960s, bringing in excess of a half-million new acres into production in the southern San Joaquin Valley. The cumulative impacts of population and income growth, urbanization, and new production opportunities opened by water transfer led to rapid and significant changes in California agriculture. The changes involved expansion both in the suite of crops produced and in alterations in the location of production. We identify three examples. First, Southern California’s dairy industry moved from southern Los Angeles and northern Orange Counties to eastern Los Angeles County and then to western San Bernardino and Riverside Counties in the 1950s and 1960s. The dairy industry eventually migrated north into the southern San Joaquin Valley, where it is now concentrated in Tulare and Merced Counties. Second, the citrus industry experienced a similar migration, first east to Riverside and San Bernardino, then north. Today, more than 50 percent of the state’s production is in Tulare County, compared to nearly 45 percent of production in Los Angeles and Orange Counties in 1950. Third, rapid urban development in the south San Francisco Bay Area pushed deciduous fruit production out of the Santa Clara Valley into the Sacramento and Northern San Joaquin Valleys. Using prunes as an example , in 1950 nearly 80 percent of the 100,000 bearing acres of prunes were on the central coast. The ratio of non-bearing to bearing acreage was “0.09”.3 By 1960, the non-bearing to bearing ratio for the state had tripled to 0.34, but in the Sacramento Valley it was an astounding 0.82. In those two decades, prune acreage in the Sacramento Valley increased from 20,000 to 50,000 bearing acres.

By the end of the century, virtually all prunes would be grown in the upper Sacramento Valley. And with this massive relocation came substantial increases in yields because of new trees, better varieties, higher planting densities, and new cultural practices. Prune yield in 1950 was 1.46 tons per acre, in 1970 it was 2.08, and in 1987 it topped 3.0 tons. Crops also moved as new water became available. One significant example is almonds. In 1950 half of the state’s almonds were grown in the Sacramento Valley, 25 percent in the San Joaquin Valley, and the remainder in coastal counties. There were 90,000 bearing acres and about 18,000 non-bearing acres geographically distributed in the same ratio as production. Yields averaged 0.42 tons per acre. Statewide in 1970 there were 148,000 bearing acres and nearly 90,000 non-bearing acres . Of these, 74,000 bearing acres and 70,000 non-bearing acres were in the San Joaquin Valley. In 20 years, yields doubled to 0.84 tons per acre. By 2000, 80 percent of production was in the San Joaquin Valley, 20 percent in the Sacramento Valley, and virtually none on the coast. Yields now average well over a ton per acre. The expanded availability of both federal and state water,large square pots coupled with relatively high federal commodity price supports, also led to rapid expansions in cotton and rice production despite generally low and declining field-crop prices in the 1950s and 1960s. Along with an increase in production, a significant change in U.S. commodity policy in 1965 rapidly increased exports of basic commodities because these exports were now priced competitively in world markets. The bottom line is that the 1950s and 1960s saw the beginning of a second fundamental transformation of California crop agriculture in terms of expansion, changing composition, relocation, and greatly enhanced yields. The dominant driver of this transformation was productivity growth. Traditional field crops, as a share of production, declined steadily, to be replaced by higher-valued, income-sensitive crops. Higher incomes plus urbanization accounted for the rising importance of fresh vegetables and horticulture products in California agriculture. Rising incomes after WWII also fueled a rapid expansion in consumer demand for beef. U.S. consumption rose from somewhat more than 50 pounds per capita in 1950 to almost 95 pounds in the mid-1970s. California’s livestock sector responded to that demand expansion in a big way. One of the most phenomenal growth patterns observed was the practice of fattening slaughter beef in confined feedlots. Cattle numbers in California had been flat from 1900 to 1940, at approximately 1.4 million head. Numbers increased to 3.9 million head in 1969—a 250 percent increase . Again, California led the nation in new approaches to large-scale agricultural production. However, by the 1970s, large-scale feedlots were established in Arizona, Colorado, Texas, and the Midwest, areas generally more proximate to Great Plains and Midwestern feed supplies. Also, per-capita beef consumption steadily declined after the 1970s, stabilizing around 66 pounds per capita in the 1990s and early 2000s. California’s second beef boom was replaced by the significant expansion of the dairy industry. In 1950 there were 780,000 dairy cows in California—19,428 farms with an average of 40 cows per farm. Average production per cow was 7,700 pounds of milk per year. In 1970 there were slightly less than 5,000 farms, nearly a 400 percent reduction, but the average number of cows per farm had nearly quadrupled to 150. Each cow now produced an average of almost 13,000 pounds per year—yields nearly doubling in 20 years.

The dairy transformation had begun. It would play out dramatically over the next 30 years so that in 2001 there were but 2,157 dairy farms with an average of 721 cows each and yielding more than 21,000 pounds of milk per cow. Production increased even more rapidly because the number of cows also increased from 700,000 to 800,000 in the 1950s and 1960s to 1,555,000 in 2001. The dairy industry emerged as the dominant commodity in the agricultural portfolio of California. In 1993 California overtook Wisconsin as the number one milk producer in the nation and now accounts for 48 percent of the U.S. nonfat dry milk production , 28 percent of U.S. butter , and 18 percent of U.S. cheese production . There are many other stories that could be told about the boom period of the 1950s and 1960s, but the picture that emerges is clear: a dynamic, demand-driven agriculture responding to each instance of production relocation with substantially increased productivity. Aided and abetted by a constant supply of new technology, agriculture in the 1950s and 1960s grew rapidly. It existed in a state that was growing very rapidly and getting rich fast. Despite this record of rapid growth, the next three decades were going to be even more explosive but also more unstable. Whereas the 1950s and 1960s were characterized by relatively stable prices, increased price volatility in the next three decades would lead to substantial swings in the profitability and economic sustainability of firms in California agriculture.As California agriculture entered the last three decades of the 20th Century, and despite ongoing growth in specialty-crop production, it maintained a predominant basic-commodity orientation. Field crops together with livestock and livestock products accounted for 56 percent of the value of agricultural sales in 1970. Basic commodities were priced in national markets, and California producers responded to these national prices and transportation differentials. Government policy supported stable prices. By the end of the epoch, less government policy emphasis on domestic prices became the norm along with wider price swings induced by rapid changes in both consumer and export demand for California’s agricultural produce. Many vegetables, fruits, and nuts were exclusively produced in California. At the very least, if not exclusive to the entire U.S. production, they were definitely exclusive during certain production seasons. Specialty crops enjoyed multiple market options , but those options would become less easily accessible over time. European and Asian economies, which were growing markets throughout this period, gradually gained increased influence over agricultural prices, making the California producer more exposed to offshore economic conditions. While foreign economic conditions were not a significant factor at the start of this period, they emerged abruptly in the mid-1970s and added considerable turbulence to agricultural markets during the 1990s.

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