Further compounding these labor-utilization issues, growers must offer a higher piecerate when productivity is low in order to retain their labor force and increased variability in available yield for harvest makes it more difficult for managers to allocate labor appropriately. The market for raspberry pickers is highly competitive. Workers who believe they can earn more money elsewhere, because less fruit is damaged, may leave during a harvest or not return for a subsequent harvest. The potential resulting labor shortage in fields with significant SWD damage could further exacerbate fruit losses due to SWD as unharvested fruit become overripe and act as a SWD breeding ground. Further, agricultural labor costs are also rising over time as the supply of labor from Mexico is shrinking due to improving economic conditions. It is difficult to observe these increased labor costs directly, but it is clear that they are not negligible. In 2015, a tray of 12 six ounce clam shells of conventional raspberries sold at an average price of $15.98 per tray based on Salinas-Watsonville and Oxnard district shipping point prices. According to a 2012 UC Davis study of raspberry production costs and returns, production costs were estimated to be $10 per tray of raspberries. Labor costs accounted for approximately half of these production costs, and the study did not report any SWD-targeting activities. The piece-rate alone averaged $4 per tray in a season.If one were to assume, conservatively, that these additional labor costs associated with managing SWD increased total labor costs by as little as 2% and 4% for conventional and organic raspberry producers, respectively, then these activities would account for a 1% and 2% increase in total production costs. Thus, a 1% increase is production costs would reduce a conventional raspberry grower’s profit margin by approximately 1.67%.

If a similar cost structure is assumed for organic raspberry producers,blueberry containers then one would expect approximately a 3.34% reduction in profit margin resulting from the additional labor costs associated with managing SWD. Labor costs are assumed to increase by a greater percentage for organic producers because they are more reliant on labor-intensive SWD control methods.We examined revenue losses and management costs associated with this invasive pest. Using a combination of field trial data and expert observations, we calculated that SWD has accounted for approximately $39.8 million in revenue losses, equivalent to 2.19% of realized revenues, for the California raspberry industry between 2009 and 2014. Conventional producers accounted for $36.4 million of these losses, equivalent to 2.07% of their realized revenues. Organic producers accounted for $3.43 million of these losses, equivalent to 5.74% of their realized revenues. SWD management activities have also significantly increased production costs for raspberry growers. We calculated that the cost of chemical purchases increased annual per hectare production costs for conventional and organic producers by $1,161.28 and $2,933.01, respectively. We also calculated that the cost of labor-intensive SWD management activities decreased conventional and organic raspberry producers’ profits by 1.67% and 3.34%, respectively. Even though the industry has managed to adapt to the pest, these revenue losses and management costs have significantly reduced the profitability of the commercial production of fresh raspberries. Looking into the future, it is unclear whether SWD will remain a threat to California’s raspberry producers. On one hand, the primary biological reason that SWD has become such an economically damaging pest in both North America and Europe following its invasion is the absence of an effective natural enemy. In Asia, where SWD originates, the presence of effective natural enemies greatly reduces damages associated with the pest. Thus, the introduction of an effective biological control agent could dramatically reduce these estimated losses in the future. On the other hand, California’s raspberry producers rely heavily on chemical management options to reduce yield losses associated with SWD infestations.

If SWD populations were to develop significant resistance to these chemicals over time or restrictions were placed on their use, then these estimated losses could increase dramatically. sitive to N fixation, moss accumulation, organic layer depth, soil drainage, and fire severity. Finally, there are several comprehensive studies of post-fire succession in Central and Eastern Canada , but the trees in these sites inhabit different soil drainage and temperature regimes than their Alaskan relatives, potentially resulting in different rates of ecosystem C dynamics . The goals of this study were to describe the changes in community structure and above ground net primary productivity and biomass that occur over post-fire succession in the upland black spruce forests of Interior Alaska. We present measurements that span two different time scales: recovery 1–4 years after fire and recovery over the entire successional cycle. For the former, we followed vegetation recovery for 4 years after the 1999 Donnelly Flats fire near Delta Junction, Alaska. We used a chronosequence approach for the latter by selecting two sequences of sites in the region that varied primarily in time since fire: a mesic sequence on moderately well-drained soil with permafrost and a dry sequence located on well-drained soils without permafrost . These sequences represent transitions in environmental factors that might occur with climate warming, including loss of permafrost and subsequent increases in soil drainage .This study was conducted in the Donnelly Flats area located near Delta Junction in Interior Alaska, in seven upland sites that were previously dominated by black spruce . All sites were located within a 100-km2 area on gently sloped alluvial flats that range from moderately well-drained soils dominated by permafrost to well-drained soils where permafrost was largely absent. Soil drainage was based on depth to water table and hydraulic conductivity . Our study include three sites on well-drained soils that burned in stand-killing wildfires in 1999, 1987, and approximately 1921 , hereafter the dry chronosequence, and four sites on moderately well-drained soils that burned in 1999, 1994, 1956, and approximately 1886 , hereafter the mesic chronosequence.

Time since last fire was determined by historical record in the younger sites and by tree ring analyses in the older sites. Some or all of these sites have been used to assess the effects of fire on soil C storage and emissions , soil chemistry , hydrogen fluxes , fungal community composition and dynamics , seasonal CO2 and 18O–CO2 fluxes and energy exchange . Within each chronosequence, sites were chosen to have similar state factors other than time . Approximately 65% of precipitation fell during June, July, and August. Potential biota: Although all stands were currently or historically dominated by black spruce and were in a close enough proximity that they belong to the same regional pool of potentially colonizing organisms, the under story vegetation and ground cover varied with soil drainage and stand age . The oldest dry stand was a lichen woodland , with ground cover dominance split between feather moss and lichens. Vaccinium uliginosum and V. vitis-idaea were the most abundant under story species, with deciduous shrubs and trees, forbs and graminoids present but at low abundance. Many of the same species resprouted or recruited after fire in the 1999 dry site and dominated the understory in the 1987 dry site. Species characteristic of well-drained ecosystems that were present in all dry chronosequence sites and absent from the mesic sites were the grass Festuca altaica and the evergreen shrub Arctostaphylos uva-ursi. These species were present, however,best indoor plant pots on trails and roadsides around the mesic sites. The oldest mesic stand had continuous feathermoss ground cover and a high abundance of Vaccinium spp. Feathermoss occupied almost the entire ground surface in the 1956 and 1886 mesic sites. In the 1994 mesic site it persisted in patches that appeared to have escaped burning. Vascular nomenclature follows Hulte´n and non-vascular nomenclature follows Vitt and others . Relief: Sites in both chronosequences were within a 100- km2 area with little variation in slope or topography . Parent material: Soils along both chronosequences were mainly derived from the Donnelly moraine and wind blown loess and have been described in detail elsewhere . Differences in drainage between the chronosequences are thought to be related to differences in water table depth and texture . Although great care was taken to control state factors within and between chronosequences, it was difficult to fully constrain the effects of past fires on productivity or biomass pools. In the 1999, 1994, and 1987 sites, fires were stand replacing . In the 1957 mesic site, the relatively small range of tree sizes suggests a single cohort of black spruce. In the mature 1886 mesic and 1921 dry sites where tree sizes are quite variable, however, the number of trees sampled for age was not large enough to determine whether stands are comprised of a single cohort . At the landscape-scale, the severity and frequency of fire are likely to be related to soil drainage . At the site level, however, stochastic factors such as weather conditions, time since last fire, and neighboring vegetation can also affect fire severity.

Post-fire vegetation recovery is similarly affected by stochastic processes such as timing of fire in relation to both vegetative and reproductive phenology, proximity of seed source, and/or the effects of past and present climate conditions on demographic processes. Finally, we caution the reader to keep in mind at all times that this is an observational study; we depend on the assumptions of the chronosequence approach to make inferences about time.We used a combination of inventory and allometric methods to estimate above ground live tree biomass and production in the sites with trees greater than 1.37 m in height, including the 1987 and 1921 dry sites, and the 1956 and 1886 mesic sites. Sixteen 100 m2 plots were established in the dry sites in four blocks with greater than 100 m between blocks, and six 100 m2 plots were established at greater than 100 m from each other in the 120- year-old mesic site . The diameter at breast height was measured on all trees in these plots. In the 1956 mesic site, tree density and DBH were estimated with a modified point-centerquarter method . When applied in the same site , these methods produced statistically indistinguishable estimates of tree density . Site-specific allometric equations were developed for black spruce in the 1921 dry site and in the 1956 and 1886 mesic sites. An aspen equation was developed for the 1987 dry site; it was also used to estimate aspen biomass in the 1956 mesic site, where aspen comprised 26% of the total basal area. In each site, 10–13 trees were selected in a semi-random manner, where initial selection was stratified to span 90% of the stand DBH range as determined by the inventories described above. All trees were harvested in August 2001. Diameter at breast height, basal diameter at moss level, and height were measured. Each tree was felled at ground level, returned to the lab and separated into dead material, stem, coarse old branches , fine old branches , cones, dead branches, old leaves, and the current year‘s leaves and stems. Aspen were separated into dead material, stem, old branches, and the current year‘s branches and leaves. These components were weighed wet and chopped into small pieces. Sub-samples were weighed, dried at 60 C until they reached a constant mass and reweighed to determine dry weight ratio. For each site, the best-fit linear equation relating the square of DBH to each biomass pool 2 except for old leaves, which was best fit by ln DBH. In all cases, DBH2 or lnDBH was a better predictor of biomass than was a DBHb . Data were log transformed if necessary to meet the assumptions of linear regression. All allometry regression analyses were carried out with Systat version 10.2 . Allometric equations were combined with plot-level inventory data to estimate biomass on a per unit area basis. Approximately 10% of the trees greater than 1.37 m in height at each site were smaller than the minimum DBH included in our equations and for these trees, we used regression equations forced through the origin . To estimate annual diameter increment increase, we analyzed tree ring width on a subset of allometry trees from each site with a microscope and micrometer.

Additional pre-registered experiments showed that subjects’ querying behavior was no more optimal – or less similaritydriven – in our active learning task than a traditional semantic search task , and no more optimal or less similarity driven when directly told to query more optimally by querying dissimilar items , suggesting that memory based active learning is at the mercy of extremely stubborn memory constraints, which are difficult to alleviate by task instructions. A final experiment showed that subjects can distinguish between the more and less optimal query sets, suggesting that subjects understand what optimality entails, but that memory constraints make the spontaneous generation of optimal queries from memory difficult. Our results stand in stark contrast with the large body of work that finds optimal search in active learning. The theory that people acquire information optimally has been very successful in explaining human inquiry in several domains. However, most prior studies use fairly simple, artificial stimuli, and do not require subjects to generate queries from memory. We thus suggest that the scope of the optimality hypothesis in explaining human active learning may be more limited than previously thought. Indeed, we suspect that any setting in which subjects must formulate sequences of queries in natural language will probably be constrained by memory processes, particularly the similarity-driven associative memory search. Although associative memory processes curtail optimal active learning, that does not mean that people’s memory processes are inherently flawed. Rather, memory serves multiple cognitive functions and the associative biases documented in this paper may reflect optimal trade offs between diverging task demands. Indeed, many researchers have argued that association or similarity-driven memory search is part of an optimal system for semantic memory retrieval . Related work has shown that associative memory processes implicated in judgment and decision biases are adaptive in that they often lead to accurate inference and generalization with minimal cognitive cost . Regulating these processes in active learning tasks may be too effortful,blueberries in pots and people may be optimally trading off performance with the cognitive cost required to succeed in our task .

This theory predicts that even though we were unable to reduce semantic congruence and increase optimal search through coaching, performance may improve with higher incentives or practice. Testing these predictions is an important topic for future work. Other future directions include the refinement of our memory and learning models. For example, subjects in our study learned about novel target properties. Yet they came into the experiments with idiosyncratic knowledge about food items or animals. Thus, it is likely they held different prior belief about the novel target properties. Since prior belief is not the focus of this paper, we assumed all subjects held the same prior belief in the experiments. In future work, the shape of prior belief can be set as free parameters and the same framework can be used to derive the prior representation of target properties in a given domain. Individual differences in this regard can be revealed. The Bayesian learning model also assumes that subjects maintain a distribution of belief over multiple hypotheses . However, other research suggests that in a closely related – and not even as complex – active category learning setting, subjects maintain a single hypothesis at a time . Previous research also reveals other simple heuristics, such as the split-half heuristic and the likelihood difference heuristic , in active learning tasks. It is possible that such heuristics play a role in the query search in our active learning tasks and, therefore, can be considered in the modeling of algorithmic processes in future research. Our work contributes to the emerging body of research that offers researchers a naturalistic search domain to study active learning. Additionally, our computational models integrate insights from several fields, and are able to jointly describe both algorithmic memory search processes as well as the optimality or suboptimality of these search processes for active learning. In this way, our paper presents a powerful new research paradigm for naturalistic active learning. There has been an increasing interest in porting computational cognitive models beyond abstract lab stimuli, to attempt to describe everyday cognition. This has been driven by the availability of new machine learning models that offer quantitative representations for natural entities , as well as the growing demand from policy makers and practitioners for theory-driven behavioral and cognitive insights.

Our research is part of this trend, and we look forward to future work that applies established algorithmic and rational theories of cognition to rich stimuli sets to better understand human cognition and behavior in the wild. The slowdown in unauthorized Mexico–U.S. migration has set off a race in U.S. agriculture between rising imports, more machines, and foreign guest workers. Trade policy, including North American Free Trade Agreement re-negotiations, and immigration policy, including more enforcement and new or revised guest worker programs, will determine the winner. Fewer and larger farms that depend on hired workers produce most U.S. fruits, vegetables, and horticultural crops such as nursery plants. The number of farms in the United States is stable at about 2 million, but the largest 10% of all farms account for three fourths of U.S. farm sales. In fresh vegetables, the largest 10 producers account for more than half of the lettuce, broccoli and carrots produced. Americans do not dream of growing up to be farm workers. About 70% of the hired workers on U.S. crop farms were born in Mexico, and 70% of these Mexican born workers are unauthorized, so half of crop workers are working illegally. California has a higher share of unauthorized workers because more of its workers were born in Mexico, 90% versus less than 70% in other states. Crop workers are aging and settling. Most have families that include children born in the United States, and few are migrants who follow the crop harvests from south to north. Unauthorized newcomers, who are primarily Mexican-born workers in the United States less than a year, have been the flexible fresh blood of the farm workforce, willing to move to fill vacant jobs. Their share of crop workers peaked at a quarter in 2000, but today such newcomers represent just 1% of crop workers. Farmers are responding to the end of large-scale Mexico–United States migration and California’s rising minimum wage with four strategies: satisfy current workers to retain them, stretch them with mechanical aids that increase their productivity, substitute machines for workers, and supplement current workers with H-2A guest workers. Seasonal farm work is generally a decade-long job rather than a lifetime career. Training first-level supervisors to reduce favoritism and harassment, paying bonuses to workers who stay through the season, and offering other benefits helps to satisfy current workers and keep them in farm work longer.

Stretching farm workers involves management changes and mechanical aids that increase productivity. Most fresh fruits and vegetables are over 90% water, and workers spend much of their time carrying harvested produce down ladders to bins or to the end of rows to receive credit for their work. Dwarf trees mean fewer ladders and faster picking, reducing the need to fill 50- to 60-pound bags of apples and oranges from tall ladders. Slow-moving conveyor belts that travel ahead of workers in the fields reduce the need to carry harvested produce, increasing worker productivity and making jobs more attractive to older workers and women. Substitution is replacing workers with machines. There are machines available to handle most tasks done by farm workers, but human hands are gentler than mechanical fingers on fragile fresh fruits and vegetables, so that a higher share of hand-harvested produce can be sent to consumers. Machines have other disadvantages as well. They are fixed costs, meaning that farmers must pay for, say, a $200,000 harvesting machine whether there are apples to pick or not, while workers are variable costs who are not paid if storms or disease destroy the apple crop. Nonetheless, rising minimum wages, fewer flexible newcomers,square plant pots and advances in mechanization have encouraged many farmers to experiment with machines, prompting manufacturers to develop and market labor-saving machines that are doing more planting and pruning and are improving rapidly to harvest blueberries, peaches and leaf lettuces. The fourth option is to recruit guest workers under the federal H-2A program, which admits an unlimited number of foreign farm workers to fill seasonal jobs. Receiving permission to hire H-2A guest workers requires farmers to try and fail to recruit U.S.-born workers, provide free housing, and pay an Adverse Effect Wage Rate , which is $13.18 an hour in California in 2018. The number of U.S. farm jobs certified to be filled by H-2A workers tripled over the past decade to 200,000 in fiscal year 2017 and may surpass the peak number of Braceros by 2025 . The number of jobs certified to be filled by H-2A workers in California tripled in 5 years, from 3,000 in 2012 to 15,000 in 2017, and appears poised to continue increasing. Half of the fresh fruit and a quarter of the fresh vegetables available to Americans are imported, and imports of everything from avocados to raspberries are rising. Mexico is the major source of fresh fruit and vegetable imports, supplying half of the imported fresh fruit and three-fourths of the imported fresh vegetables. Many of the fruits and vegetables imported from Mexico are produced on farms that involve partnerships between U.S. and Mexican growers and shippers, with U.S. partners providing capital and technology and marketing Mexican-grown produce. Satisfying and stretching current workers are shorter term strategies to increase the productivity of an aging farm workforce. Substituting machines, hiring guest workers, and increasing imports are longer term strategies to supply fresh fruits and vegetables to Americans.

Policy will help to determine the winner of the race in the fields between machines, migrants and imports. Technologies that could replace farm workers are improving rapidly and decreasing in cost, potentially putting agriculture on the cusp of another wave of labor-saving mechanization. Farmers have long sought new or revised guest worker programs that eliminate requirements to try to recruit U.S.-born workers, provide housing, and pay the super minimum AEWR wage. The House Judiciary Committee approved a bill in November 2017 that includes these farmer wishes, but it has drawn opposition from advocates for removing worker protections and from some farmers for capping the number of guest worker visas at 450,000 a year. If the new H-2C program included in the Agricultural Guest worker Act is enacted, the influx of farm guest workers would likely accelerate, which may reduce support for the engineers and scientists developing machines to replace farm workers. The United States has an overall agricultural trade surplus, but a deficit in agricultural trade with Mexico reflecting ever-more Mexican avocado, tomato and berry imports. The Trump Administration aims to reduce the trade deficit with Mexico in NAFTA renegotiations, perhaps by imposing tariffs or other restrictions on Mexican imports. This could slow the integration of the North American produce industry, which has evolved to provide year-round supplies of fresh fruits and vegetables to Americans. Agriculture has been at farm labor crossroads many times, asking who will pick the crops after the exclusion of the Chinese in the 1880s and the termination of the Bracero program in the 1960s. Today’s race in the fields will determine whether Americans will consume more imported produce or whether fruits and vegetables will continue to be grown in the United States and picked by machines or guest workers. Lowbush “wild” blueberries are considered a nutrient-rich healthy food, due in large part to their exceptional phenolic content and antioxidant activity. Lowbush blueberries are particularly rich in anthocyanins and the anthocyanin profile is complex compared with other fruits. They contain five of the six anthocyanidins commonly found in nature , which can have three different sugar moieties attached as well as acyl groups such as acetyl-, malonyl-, or coumaryl- also attached to the sugar moieties. Blueberries are also rich in proanthocyanidins, chlorogenic acid, and flavonols. Diets rich in blueberries or their polyphenolic-rich extracts have been associated with lower cardiovascular risk, weight gain and metabolic syndrome, and neurological diseases . In addition, studies involving blueberries have identified polyphenolic-derived phenolic acids that improve cell differentiation and proliferation of osteoblasts in vitro and promote bone growth and limit bone loss in rodents. These health-promoting effects are due to a myriad of mechanisms associated with blueberry polyphenolics, including prevention of oxidative stress and inflammation, and vaso- and lipid modulation.

Given the strong linkages between the agriculture sector and the other sectors of the economy, it is important to not only estimate the direct effects of pest damage but also the multiplier effects, because damage to crops by birds and rodents reduces the output of the agriculture sector and all other linked sectors. In general, the economic effects of a change in producer costs are usually broken down into three different categories: direct, indirect, and induced effects. The direct effect of a lower yield can be measured by the revenue lost that the grower would have earned from sale of that acre and the increase cost of pest control. For example, the direct effect of bird damage to an almond orchard would be the value of the damaged and eaten nuts and the farmer’s control costs. However, the revenue of individual growers supports other industries in the economy. Growers create jobs for shop owners, restaurant staff, police, fire, etc., which must also be measured when examining the total economic effect. These additional non-direct or multiplier effects are called secondary economic impacts and are composed of indirect and induced effects. Several studies exist that use IO models to estimate the total impact of California agriculture to the state economy , but no study exists using this model to analyze specifically the total impact of bird and rodent damage to these crops. This paper details the initial determination of the counties and crops that will be used in an IO model to estimate the total economic impact of a group of pests, birds and rodents, on California agriculture. The results of this study is a list of counties that will represent a segment of California’s agricultural production that has a high value and concentration of crops that are susceptible to bird and rodent damage. Ultimately, in subsequent phases of this study, IO modeling will determine the loss of employment and revenue to the regional economy created by birds and rodents.

Identification and accurate measurement of bird and rodent damage to crops has progressed; however, pest arrival, density,growing raspberries in containers and potential and real damage to crops is still an uncertain event at the farm level. Additionally, pesticide use and productivity varies across time and space . To more effectively limit pest dam- age, increased use of Integrated Pest Management tools in California agriculture suggest that California’s pesticide use levels for most crops are low relative to the rest of the United States . There are several important outcomes that emerge from this research on the economic impact of bird and rodent damage to California crops. A useful way to quantify the economic effects, which are likely to occur within the region as a result of change in agriculture expenditures resulting from increased costs and decreased yield due to bird and rodent damage, is through IO modeling. Many governments, agricultural associations, and others benefit from IO modeling but face limited budgets. The methodology presented in this paper is useful for the narrowing of an economic analysis, so that the regions or counties chosen for the analysis provide the most pertinent and valuable results for the stakeholder. Additionally, the results of this economic research can be used at the state level to advocate, in revenue and jobs lost terms, for additional and more effective pest control options. Fluvial suspended sediment fluxes from developed watersheds in semi-arid environments are influenced by natural and human induced changes to the land surface that interact with extremely variable climatic regimes. Environmental monitoring and sedimentary records indicate that fluvial sediment flux dynamics often exhibit temporal dependence over event to interdecadal time scales, particularly in arid to semi-arid climates . However, attributing changes in sediment regimes to a discrete cause is often complicated by the overprinting of many external drivers and internal dynamics that affect watershed scale sediment production and transport, which tend to obscure the effects of individual forcing factors . Furthermore, factors affecting watershed-scale sediment production operate over a wide range of time scales, with even seemingly discrete events generating legacy effects that may last for years or decades .

Semi-arid basins in particular have been found to display persistent dependence on climatically driven antecedent basin conditions, such as storm/flood and wildfire histories . The addition of human influences further complicates sediment flux controls in the highly developed portions of the world that are the most intensively studied . Thus, elucidation of temporal dependence in the suspended sediment dynamics of a highly developed, semi-arid basin is a forensic exercise of implicating and eliminating a host of potential controls. For this reason, when discrete controls on sediment dynamics are discovered in a given watershed it is often the result of scenarios where proportionally large areal disturbances have dominated the sediment response of relatively small watersheds. In this way, wildfire , urbanization , and agriculture have been found to exert significant control on fluvial sediment flux. However, understanding the fluvial sediment dynamics of most systems over inter-decadal time scales requires the disentanglement of multiple controls, particularly at larger spatial scales.The most important external driver controlling inter-decadal scale sediment flux is regional climate, which interacts with internal factors such as geological substrate and topography to influence internal processes such as geomorphic evolution, soil development, vegetation assemblages, and fire frequency . The interaction of vegetation, topography and interannual to decadal scale climatic expression also largely determines wildfire regimes . Sediment flux generally rises after wildfire due to increases in the erodibility of hillslope surfaces through the removal of vegetation and litter layers, destabilization of soil aggregates by organic matter combustion, and increases in soil mantle slides or overland flow due to the development of subsurface and surface soil hydrophobicity, respectively . In systems experiencing dry seasons, such as much of the Western U.S., this results in down-slopedry-ravel transport through gravity alone . Soil heating can also cause hydrophobicity increases in the soil surface that, along with decreases in interception and evapotranspiration, cause increases in surface runoff during the wet season . Increased surface runoff further exacerbates erosion from the destabilized hillslope. Indeed, the timing of high-intensity precipitation plays a large role in post-fire sediment flux augmentation .

Large storms produce precipitation intensities and volumes sufficient to traverse runoff regimes, from sheet flow, to rill and gully erosion, and mass wasting, which can very effectively erode wildfire destabilized hillslopes . With increasing elapsed time between wildfire and high intensity precipitation events, hillslopes generally re-vegetate, re-stabilize, and yield less sediment for a given precipitation magnitude , although decadal scale legacies of individual fires have been reported . Humans have caused pre-historic to historic increases in global sediment flux due largely to agriculture and deforestation . This phenomenon has generally been followed by a rapid decrease in sediment flux during the 20th century, primarily from river impoundment, and to a lesser degree changes in agricultural practices and afforestation . Changes in agricultural practices over the last century have in many cases led to decreases in off-field sediment transport with the implementation of soil conservation practices, including changes to less erosive irrigation techniques . Flow regulation causes declines in basin scale sediment yield by trapping sediment in reservoirs and altering the natural flow regime, particularly through reduction of peak flood discharge magnitudes . After an initial spike during construction, urbanization can also lead to sediment load decreases with the increase in the cover of impervious surfaces . Conversely, extensive urbanization can act to increase sediment yield by altering basin scale precipitation – discharge characteristics ; for example shortening the time to peak flow,large plastic pots for plants decreasing total flow duration, increasing peak magnitude, and increasing total runoff volume .Due to the difficulty and expense of collecting samples, fluvial suspended sediment flux is usually estimated on the basis of infrequent sediment monitoring coupled with more frequent or even continuous discharge monitoring . The most common technique is to compute sediment concentration -discharge rating curves using log-linear regression or non-parametric localized regression methods such as LOESS . Anthropogenic disturbances and wildfire will alter CSS–Q relationships if they result in disproportionate changes in the magnitude and/or timing of the supply of sediment or water relative to one another . Thus, changes in sediment flux and CSS-Q relationships examined in relation to agriculture and wildfire activity over time can provide insight into these important controls onsediment dynamics in highly agricultural, semi-arid basins.

Determination of the dominance of a factor potentially controlling sediment production over other factors can be approached through the comparison of the temporal trends of control metrics with the metric describing sediment production. Correlation between control factors and sediment production metrics can then be analyzed and interpreted in light of the expected effects of a given control .The objective of this study was to examine how contemporary wildfire activity and land use change affected discharge normalized sediment delivery from highly agricultural, semi-arid mountainous watersheds in the context of additional hydrologic and climatic controls. The fundamental approach was to examine changes in suspended sediment – discharge relationships over time in light of temporal trends in wildfire and agricultural activities. Conversely, changes to less erosive agricultural technologies, such as increasing the proportional utilization of drip irrigation, would be expected to result in decreasing sediment production. Departure of sediment production trends from those expected on the basis of changes in a given control factor would be considered as evidence that the factor was not a dominant control on sediment production. Correlation of sediment production metrics with wildfire activities were then used to determine if wildfire disturbance also acted as a short term control on sediment production. Wildfire activity was expected to correlate positively with sediment production. Departure from this expected correlation between sediment production and wildfire would also indicate that wildfire was not a dominant control.The Salinas River drains 11,605 km2 of the Central Coast Ranges of California from a maximum relief of ~ 1,900 m with a mean discharge of 11.6 m3 /s from the lowest gauge in the basin for the periods of 1931- 2011 . The regional climate is dry-summer subtropical — most annual precipitation falls as rain originating from winter storms, the largest of which often occur during strong El Niño years . For this region ‘water years’ begin on 1 October of the previous calendar year and end on 30 September of the calendar year. A strong precipitation gradient extends from the wetter SW to drier NE region of the watershed due to predominant S-SW impingement of storms and orographical forcing . Geologic substrate is primarily Mesozoic sedimentary rock . The Salinas River valley consists of three lateral geomorphic zones – a riverbed, a bottomland, and flanking terraces, with one such terrace containing the major alluvial plain on the valley floor that is populated and used today. The bottomland is a broad bench situated lower than the surrounding plain and separated from it by well-defined side slopes. Though historically there was a well-defined, small, forested channel localized in the bottomland , today the channel is primarily a broad, destabilized active zone that is intermittently well-defined in space and time as either a meandering thread or braided channel. The modern channel is lightly vegetated, with the abundance depending on the duration of interannual dry periods between floods, as these times allow pioneer grasses and willow shrubs to emerge though not necessarily persist. The Salinas valley has been influenced by humans and animals throughout its recorded history and likely thousands of years before the arrival of Europeans. Pre-historically, the Ohlone natives of the region used fire to maintain an open terrain on the main valley floor and to promote their food supply, whereas the hills and mountains around the valley were forested and home to large predators . The moist bottomlands were well vegetated with cottonwoods, sycamores, live oaks, willows, and some pines and white oaks . Archival records and drawings from the Spanish and Mexican era indicate that the bottomlands were deforested in support of the development of the rancho economy prior to American conquest. Further, beaver were likely abundant in the river and important in its morphology and sediment dynamics, yet are now demonstrated to have been extirpated from the landscape as part of the maritime California fur trade during the Spanish and Mexican era . Meanwhile, the higher plains adjacent to the bottomlands were grazed by some millions of free-ranging cattle during this era , until the devastating drought of 1861-1865 ended California’s cattle-based economy.

Due to the fact that only a very small number of microbes can be reliably cultured for further study towards using them as legume crop inoculants, we focused on the PGPB that the plant specifically selects within its root nodules with the goal of finding “helpers” for the nitrogen-fixing rhizobia in supporting plant growth. Soil collections were made in 2017 and 2019 from the farm of the Botswana University of Agricultural and Natural Resources in Notwane from underneath an indigenous Tephrosia purpurea plant . Environmental DNA was isolated from both samples in 2019, at the same time trap experiments were performed, to provide insight into the diversity of the soil microbial community. It should be noted that there was a two-year gap between collecting the 2017 sample and its analysis in contrast to the 2019 sample that was analyzed almost immediately after collection. Because the methodology for DNA extraction was the same, we hypothesized that differences in the percentages of the phyla might occur from changes brought about by storage conditions, or time elapsed. In both the 2017 and 2019 samples, the major phyla were Proteobacteria, Firmicutes, and Actinobacteria. The percentage of Actinobacteria in the 2019 soil was almost twice that of the 2017-collected soil . These results are in line with those obtained by other authors. The bacterial genera responsible for the induction of N2-fixing nodules in legumes belong to the phylum Proteobacteria and are therefore part of the dominant group. The phyla Actinobacteria and Firmicutes contain several genera of bacteria with PGPB activities that are very well documented. The percentages of Gemmatimonadetes, Acidobacteria, and Planctomycetes also varied between the 2017- and 2019-analyzed samples . Whether or not these differences are due to the delay between collection and analysis or other factors such as changes in the surrounding environment such as water content is not known. Nevertheless,plastic pots for planting the data demonstrated that the dominant microbes from the eDNA analysis were Proteobacteria, Firmicutes, and Actinobacteria, all of which are more likely to be cultured and serve as inoculants than the other bacteria listed.

Soil isolates are often considered as sources of inoculants for crops in agriculture, particularly rhizobia and other plant growth-promoting bacteria , but the nodule isolates may be a more specific inoculant for because they are found within nitrogen-fixing nodules. Evidence based on coinoculation experiments with rhizobia also indicates that soil-isolated as well as nodule-associated bacteria may be important for improving plant growth via plant nutrition. Although a large number of soil isolates have been tested for their ability to produce siderophores, solubilize phosphate, fix nitrogen, or perform other plant-growth promoting functions, to our knowledge only a few of them have been actively incorporated into agricultural practices. Due to the sheer numbers of soil isolates potentially available in Botswana soils , we focused our study on microbes housed in legume nodules. Several trap plants, including Vigna unguiculata , Macroptilium atropurpureum , and Tephrosia virginiana, nodulated following inoculation with Botswana soil mixed with an artificial substrate watered with -N medium, but cowpea gave the most consistent results . Bacteria isolated from cowpea nodules included rhizobia , which are known to nodulate cowpea and other legumes . Furthermore, species of Bacillus, including B. safensis and B. pumilus, well known PGPB, were also isolated from cowpea nodules . In addition, several possible opportunistic pathogens including Ochrobactrum anthropi, Burkholderia dolosa, Ralstonia mannitolytica, Staphylococcus pasteuri and others were isolated from cowpea nodules and identified by rrs sequencing. These emerging pathogens, which are often found in plant rhizospheres, were discarded. Non-pathogenic isolates were tested for PGP traits and their ability to grow under salinity stress and at different pH values . A number of isolates exhibited possible PGP activity including phosphate solubilization and siderophore production. Cowpea plants grown in the 2017 Botswana soil sample were harvested after 9 weeks of growth. Control +N plants produced more biomass as measured by dry weight than plants from all other treatments, averaging 1.73 g. The experimental plants were darker green in color than control -N plants and produced more than twice as much biomass, averaging 1.11 g compared to 0.47 g for the -N control.

Cowpea plants grown in the 2019 Botswana soil sample were harvested after 12 weeks of growth because of a lag in growth at the start. Control +N plants were larger, more robust, and darker green than experimental or control -N plants, averaging 0.77 g. Although the experimental plants were not as robust as the +N control plants, a result frequently observed in control plants given super-optimal N, the inoculated cowpeas produced significantly more biomass than the -N controls. All experimental cowpea plants from both soil treatments developed multiple, pink colored root nodules, whereas control -N and control +N plants were devoid of nodules. In both experiments, control -N plants were indistinguishable from control plants grown in soil that was sterilized by auto claving .Because cultivation methods are biased for the reason that very few bacteria are capable of growing on standard bacteriological culture media, we analyzed the cowpea nodule microbiome by isolating eDNA from the nodule tissue and sequenced the eDNA with the goal of obtaining an inventory of the nodule microbial population. We predicted that these analyses would give us insight into the bacteria that were specifically selected by the plant and if they were culturable, they might have potential to be used as commercial inocula. As expected from anatomical studies of determinate nodules such as cowpea, the nodule interior based on eDNA analysis is dominated by Bradyrhizobium spp. . Although DNA sequences from numerous bacterial genera including Microvirga, Rhizobium, Bacillus, Sphingomonas, and others were detected in the nodule microbiome in this study , the exact percentages and diversity of non-rhizobial microbial sequences within the nodule itself are difficult to assess. Nonetheless, several of the genera in the nodule microbiome analysis directly correspond to the nodule isolate genera. The bacterial population of nodules based on sequencing the isolated eDNA differs in terms of representation from the results obtained from isolating microbes from soil. The soil population is dominated by Actinobacteria, Proteobacteria, and Firmicutes . Although a large number of Gram-positive species are detected in the soil microbiome analysis, they are detected at very low levels in the nodule microbiome .

Nevertheless, some genera such as Bacillus as well as actinomycetes, especially Micromonospora, are repeatedly isolated from nitrogen-fixing nodules and also detected in the nodule microbiome analysis. Coupled with the fact that several of these species, when inoculated with rhizobia frequently enhance the symbiosis,drainage for plants in pots this strongly suggests that they have a positive effect on the symbiosis. The difference between the soil and nodule microbial populations in terms of numbers of microbes is reminiscent of the differences in the numbers of bacteria found in the rhizosphere versus the endosphere and between the rhizosphere and rhizoplane communities in other plant systems such as pepper and maize. Whether or not this is a specific selection for a large number of beneficial bacteria to protect the root or leaf surface from pathogen attack as suggested by the camouflage hypothesis or that normally surface bacteria are excluded from internal tissues and only some of the bacteria that enter roots and nodules are “cheaters” is difficult to determine at this time. In contrast, rhizobia are actively selected by the host plant for their symbiotic traits in response to active recognition between the host and its symbiont. Whether a similar recognition system operates between PGPB and plant surfaces is not known. Although the mechanisms used by the non-rhizobial endophytes to enter the root and the nodule frequently involve the secretion of hydrolytic enzymes such as cellulase and pectinase, are these enzymes induced because the bacteria are recognized, and if so, what are the signals to which the endophytes are responding? To our knowledge, the mechanisms underlying how a coinoculation between rhizobia and PGPB triggers plant growth stimulation are not well understood. There is now a large literature examining the impact of climate change on agricultural yields that can be divided into two types of studies. A second category that has been developed more recently looks at statistical relationships between climate or weather and crop yields. The benefits of the former are that it is grounded in a mechanistic, bottom-up understanding of how plants grow. But process-based models are often calibrated to specific field settings which can be data intensive and means the generalizability of results to larger areas is unclear.

Statistical models are typically based on observations of crop growth over large areas in real-world field settings. But the reduced-form relationship between weather variables and yield means the mechanisms driving model results are often unclear and that care should therefore be taken in using results for climate change projections extending beyond the historical record. Despite the fact that both approaches seek to quantify the impacts of climate change on agricultural productivity, there have been relatively few attempts to systematically compare findings. A number of studies have compared process-based and empirical responses for individual crops in individual locations, such as maize and wheat in South Africa or maize in Switzerland . At the global level, Liu et al provide a systematic comparison of the temperature response of wheat yields estimated from regression models, up scaling point estimates from an ensemble of process-based models, and gridded process-based models, generally finding only small differences between the three methods. In this special issue, Lobell and Asseng compare individual published estimates of crop sensitivities to climate impacts from process-based and empirical yield models, finding little difference in the temperature response. Roudier et al , Knox et al , and Knox et al are perhaps most similar to the analysis presented here. These papers present meta-analyses of yield impacts for multiple crops in specific regions and report average differences between process-based and empirical estimates. All papers find that the effect of impact estimation technique is small relative to other sources of variation. Our approach adds to these studies firstly by performing a global analysis and secondly by using a multivariate regression for our meta-analysis, instead of simply splitting the sample of studies. This multivariate approach allows us both to control for potential confounding variables and to estimate continuous response functions that can be globally extrapolated in order to inform an economic analysis. In the agricultural sector, the effect of climate change-induced yield shocks on more policy-relevant variables such as prices, consumption, food-security, and economic welfare will be mediated by the global trade in agricultural commodities and will depend on terms-of-trade effects and the interaction of climate change impacts with existing market distortions . Though several papers have incorporated climate productivity shocks into partial- and general-equilibrium models very few report welfare changes . Understanding the welfare impacts of climate change-induced productivity shocks on agriculture is important both for policy and because the simple integrated assessment models used to calculate the social cost of carbon use damage functions that parameterize changes in economic welfare with temperature. Current agricultural damage functions in these IAMs use studies from the early-to-mid 1990s that are now dated and largely obsolete . This paper contributes to the existing literature in two ways. It is the first systematic, multi-crop, global comparison between empirical and process-based crop models. Although the distinction between these approaches has been widely discussed, this paper quantifies this difference at the global scale and puts it in the context of other uncertainties in future climate change impacts, such as how quickly farmers are able to adapt to climate change. In addition, we advance the literature by examining not just yields but also economic welfare by incorporating estimated yield changes into the Global Trade Analysis Project CGE model, thereby producing results ready to inform IAM damage functions.The basis of the yield-temperature response functions in this paper is a database of studies estimating the climate change impact on yield compiled for the IPCC 5th Assessment Report , also described in a meta-analysis by Challinor et al . This database contains over 1700 point estimates of the impacts of changes in temperature, rainfall, and CO2 concentrations on the yield of 17 different crops compiled from 94 different studies.

It plots the agricultural employment in Brazil, from 1960 to 2010, separately for different ten-years birth cohorts. Following a cohort of individuals as they age, we see that fewer and fewer of them work in agriculture: this suggests that the returns from agricultural production has decreased over time, thus pushing workers to reallocate. At the same time, if we compare across cohorts in any single year, we see that the younger ones have a smaller fraction of the workers in agriculture, suggesting that – due to their higher human capital – they have a stronger comparative advantage towards non-agriculture. Over time, higher human capital cohorts enter the labor market and replace lower human capital ones, thus contributing to an aggregate decrease in agricultural employment. Not all countries look like Brazil. As a comparison, in Figure 1b we plot a similar graph for India: in this case, within cohorts reallocation over time is mostly muted, while we still observe sizable across-cohort reallocation. In this paper, we systematically document this heterogeneity across countries, and exploit it to draw general conclusions on the role of human capital. More in general, however, the simple insight on the map between reallocation by cohort and human capital might fail, since cohorts possibly differ for aspects other than their human capital. In particular, younger cohorts may face lower mobility frictions to change sector. A core contribution of this paper is to develop a simple model to analytically characterize how the reallocation within and across cohorts can be used to back out the role of human capital, taking into account both mobility frictions and general equilibrium interactions across-cohorts. Equipped with the model, we use micro-level data for 52 countries to systematically document new facts on reallocation by cohort,square plastic planter along the lines of what just described for Brazil and India.

We then use data and theory together to back out the role of human capital and to show our two main results: human capital explains, on average, approximately one third of labor reallocation; but it does not explain why some countries have faster reallocation than others. We also show that mobility frictions play a minor role, which is instrumental in using reallocation by cohort to derive the main results. Finally, we turn back to schooling, and compare our approach with a direct measurement of human capital stocks using schooling. The two approaches are complementary.The paper is organized in four sections. In Section 2 we present a dynamic overlapping generation model. The model provides an accounting framework to leverage labor reallocation by cohort to quantify the relative role of human capital in aggregate labor reallocation out of agriculture. The general features of the model are the following: time is discrete; a finite number of cohorts are alive at each point in time; each period a cohort of individuals is born and enters the labor market and one dies; individuals are heterogenous in their human capital both within and across cohorts; average human capital grows across cohorts at a constant rate; there are two sectors: agriculture and non-agriculture; agriculture uses land and labor to produce; non-agriculture uses human capital; agricultural relative price and productivity, which give the relative revenue productivity, are exogenous and decrease at a constant rate; individuals choose, in each period in which they are alive, in which sector to work subject to two mobility frictions: a one time fixed cost to be paid to change sector, and an iceberg-type cost that reduces the monetary value of non-agricultural wage each period; markets are complete and competitive. We analytically characterize the equilibrium, which displays sorting across sectors, both within and across cohorts, and labor reallocation out of agriculture. We provide three sets of theoretical results. First, we show that the rate of labor reallocation out of agriculture is constant, does not depend on either mobility friction, and is increasing in the growth rate of relative non-agricultural revenue productivity, and in the growth rate of human capital across cohorts.

This result highlights the two core forces that lead to labor reallocation out of agriculture: decrease relative agricultural price and productivity; increase in human capital. Second, we decompose the rate of labor reallocation in two components: a year effect, which captures the rate at which a given cohort reallocates out of agriculture; and a cohort effect, which captures the gap in agricultural employment across cohorts. And we show that, absent mobility frictions and ignoring general equilibrium, the year effect pins down the relative contribution of prices/productivity, while the cohort effect pins down the relative contribution of human capital accumulation. This special case corresponds to our simple insight on the role of reallocation within and across cohorts. However, in general, mobility frictions and general equilibrium complicate the analysis, by tying together year and cohort effects. The theory provides further useful guidance: we show that only fixed costs are relevant to determine labor reallocation by cohort, and that old workers are more likely to be constrained by a fixed cost, since they have fewer periods to depreciate it over. As a result, comparison of labor reallocation rates across age groups informs us on the size of the frictions. Third, in search of additional ways to discipline the size of the mobility frictions, we describe how they affect the agricultural wage gap. We show that the wage gap for movers out of agriculture can be used to identify iceberg-type frictions – such as amenity costs that have to be paid each periods. However, we also show that fixed-cost-type frictions, which are the more relevant ones for our purpose, since they affect the map between cohorts effects and human capital, cannot cannot be inferred from wages. In fact, a small wage gap for movers out of agriculture is consistent with an arbitrarily large fixed cost. In Section 3 we turn to the data. In this section we describe three novel empirical results,leaving their interpretation through the lens of the model to Section 4. We use micro level data available from IPUMS international for 52 countries around the world. The data are either censuses or large sample labor force surveys representative of the population. For each country, we have at least two repeated cross-sections distant 10 years apart. On average, for each country there are 28 years from the oldest to the most recent cross-section. For some countries, such as Brazil, our data cover half a century of labor reallocation.

The 52 countries cover roughly 2 3 of the world population, and span five continents and the income distribution from Liberia to the United States. For each country, we compute year and cohort effects as defined in the model. On average, year and cohort effects are of similar size, thus giving our first empirical result: the across-cohortsreallocation accounts on average for approximately half of the overall labor reallocation out of agriculture. The year effects are strongly correlated with the rate of labor reallocation, while the cohort effects are more similar across countries, and less strongly correlated with the overall rate of reallocation. Formally, we decompose the cross-country variance of the rate of labor reallocation and show that differences in the across-cohorts reallocation explains approximately one quarter of it, which is our second empirical result. Finally, we compute for each country, the year effect separately for individuals of different ages, and show our third empirical result: individuals of different ages have similar year effects. Section 4 uses theory and data together to decompose, in an accounting sense, the relative roles of human capital and prices/productivity for labor reallocation out of agriculture. First, we show that, without taking a stand on the size of the frictions or the strength of general equilibrium,square plastic plant pot we are able to provide an upper bound to the relative contribution of human capital: the first empirical results above directly implies that human capital accounts for at most half of average labor reallocation. That is, absent human capital accumulation the average rate of labor reallocation out of agriculture could be as low as just half the observed one. Second, we use our theoretical results to infer a value for the mobility frictions, and thus be able to provide a point estimate for the role of human capital in partial equilibrium. To back out the size of the friction, we follow two different approaches. First, we use the prediction on reallocation rates by age: the third empirical result above is not consistent with sizable mobility frictions, which would imply that old individuals reallocate at slower rates. Second, we show that, under the assumption that the mobility friction is constant within a subset of countries, the second empirical result above is not consistent with sizable mobility frictions either: mobility frictions tie together the cohort and year effects, and thus would predict that countries with faster labor reallocation have both larger year and cohort effects. The data reject this hypothesis as well. Therefore, both approaches are not consistent with a large role for frictions. In fact, we show that, in partial equilibrium, human capital accumulation accounts for 37 − 56% of average labor reallocation, depending on the chosen estimate for the frictions. Third, an elementary calibration exercise suggests that the general equilibrium forces are unlikely to overturn the quantitative results: taking into account general equilibrium reduces the role of human capital accumulation to 19−52%. Using our favorite estimates for the size of the friction and for the GE calibration, we obtain that human capital accounts for approximately one third of labor reallocation out of agriculture. Fourth and last, we focus, rather than on the average rate of labor reallocation, on its variance across countries.

We show that, while human capital explains a sizable fraction of labor reallocation on average, it has at most a minor role in explaining why some countries have faster rate of labor reallocation than others. Finally, in Section 5 we turn back to the usual approach of the literature and exploit schooling as a direct measure of human capital. Using schooling is useful for two purposes. First, it allows us to validate the main empirical approach, by showing that our model-inferred human capital stocks align well with direct measurement through schooling, both in levels and in changes across cohorts. Second, using schooling enables us to provide a proof of concept on the possibility that policies designed to increase human capital can trigger labor reallocation out of agriculture. We follow closely Duflo and exploit the INPRES school construction program in Indonesia as an exogenous variation in schooling. We show that the exogenous increase in schooling decreased the agricultural employment of the affected cohorts.We draw upon insights from a rich literature on related topics. We here discuss our contribution relative to the most closely related articles. Our work builds on the seminal work of Caselli and Coleman II and Acemoglu and Guerrieri . To our knowledge, Caselli and Coleman II first recognized the interaction between aggregate changes in human capital and structural change. It noticed that non-agriculture is more skill-intensive than agriculture, and, therefore, an aggregate increase in schooling raises the relative supply of non-agricultural workers. It focused on the effect of human capital increase on relative wages, and argued that taking it into account is necessary to match the path of relative agricultural wages. Acemoglu and Guerrieri formalized the general insight that changes in the relative prices of inputs may lead to structural transformation if sectors vary in the intensity with which they use inputs. In its analysis, Acemoglu and Guerrieri considered capital and labor as the two inputs of interest. We owe to these two papers the broad notion that human capital accumulation may be relevant in explaining reallocation out of agriculture. Relative to their work, our contribution is to provide an accounting framework and to use reallocation by cohorts to separately account for the role of human capital relative to the role of relative agriculture prices/productivity . As discussed in the introduction, the recent literature that studies the cross-sectional allocation of heterogeneous workers to sectors motivates us to interpret human capital accumulation as a change in the relative supply of agricultural labor.At the same time, in our work we bundle together the traditional views of structural change that focus on demand or supply of agricultural goods, since they both similarly affect the relative revenue productivity of agriculture, hence the demand for agricultural labor.

The sorption improvements were attributed to NaOH breaking down the lignin encapsulating cellulose or hemicellulose, thereby increasing the exposure of cellulose for reaction. Creation of tiny fissures on the treated rice straw surfaces enlarged the surface area, thereby increasing ciprofoxacin retention via physical adsorption. In an analogous study, NaOH treatment of wheat straw increased sulfonylurea herbicide retention resulting in a maximum adsorption capacity as high as 337.22mg g−1 . Alkaline treatment increased both the surface roughness and functional surface activity due to hydrolysis of esters. These changes strengthened the interactions between the alkaline-treated straw and chlorsulfuron through H-bonding, ion exchange and complexation reactions. Notably, alkali treatment is operationally straightforward; however, excessive alkali concentrations should be avoided as excess alkali can degrade the functional group content as demonstrated for wheat straw .Acidification is a wet oxidation process that can remove mineral impurities from agricultural wastes and further improves the acidic behavior and hydrophilic nature of the adsorbent surface . Common reagents for acid modification include H3PO4, HCl, HNO3 and H2SO4. During treatment, acids dissolve constituents reducing the tortuosity of the porous structure and increase the O content of the material. In particular, acid treatment promotes cellulose hydrolysis of agricultural wastes creating a more reactive material . Tevannan et al. demonstrated that HCl reduced the mineral content of barley straw; Al, P, Mn, Cu and Zn concentrations decreased by 2.28%~9.80% after acid treatment. This reduction of mineral content contributed to increased adsorption of Ni2+ from solution due to decreasing competition among cations for adsorption sites.

Generally, lignocellulosic adsorbents have low adsorption capacities for anionic pollutants due to their negatively charged surfaces. However,25 liter pot case studies have demonstrated that acidification can improve the adsorption performance for anionic pollutants as well . They ascribed this phenomenon to HNO3 treatment promoting non-electrostatic interactions between adsorbent and adsorbate, such as van der Waals and H-bonding mechanisms. Dilute acids increase the amount of C-H, O-H and C-O groups on agricultural wastes. The main functional groups in modified rice straw after HCl treatment were O-H and C-O groups, which facilitated the adsorption of 2-chlorophenol . Concentrated acids can effectively convert hydroxyl and aldehyde groups to more oxidized groups, such as the carboxyl moiety. H2SO4-oxidized coconut shell had relatively high C and O contents due to the release of volatile compounds during acid oxidation . The surface of the treated material was surrounded by COO− and SO3 − groups, which were highly effective for the adsorption of methylene blue. Further, the O content of HCl- and HNO3-treated agave bagasse increased by 4.9% compared with the raw material due to an increase of carboxyl groups . Notably, concentrated acid oxidation was shown to decrease the surface area of oxidized coconut shell due to strong corrosion, which may reduce the porosity and efficacy of the adsorbent material for retention of some pollutants . Several studies have demonstrated the efficacy of acid treated agricultural wastes for heavy metal ions, such as Zn2+, Pb2+ and Cr6+ . Acid treatment alters functional groups and several surface area/porosity characteristics to enhance adsorption performance . The adsorption capacity of natural corncob for Cd2+ increased from 4.7 to 19.3mg g−1 when the material was acidifed by HNO3 . The Cd2+ was adsorbed mainly by the carboxylic sites through ion exchange and the adsorption capacity increased directly proportional to the concentration of carboxylic sites. Te glycosidic bonds of cellulose and hemicellulose are broken down to produce aldehyde groups and eventually carboxylic groups during acidic modification.

Similarly, the maximum Cu2+ sorption capacity of HNO3-treated corn cob was 3-fold higher than that of the raw corn stalk . The pHPZC for modified corn stalk was 3.3, which was lower than that of untreated material due to the increase of O-containing groups. The acid-modified adsorbent also showed a lower separation factor than raw corn stalk , Acid-treated agricultural wastes are also effective for removal of several organic pollutants. Attainment of adsorption equilibrium for Basic Red 18 and methylene blue by HNO3- and H3PO4-modified oreganum stalks was much shorter than that of the corresponding non-treated stalks . The more rapid kinetics were ascribed to increased surface area and reactive functional groups after acid treatment, which created enhanced electrostatic and hydrophobic interactions between adsorbents and adsorbates . The results showed that the maximum adsorption of Victazol orange 3R dye to dilute HCl-treated mango seed increased from 36.9 to 63.3mg g−1 with much faster sorption kinetics than the untreated seeds owing to increased BET surface area and average pore diameter . Overall, acid treatment contributes greater functional group reactivity and structural properties to enhance adsorption performance.Esters are generated from the esterification of free hydroxyl groups in cellulose by reacting with one or more carboxyl groups , whereby cellulose reacts as a trivalent polymeric alcohol . Succinic anhydride, EDTA dianhydride, citric acid anhydride and maleic anhydride are widely used for esterification reactions, thereby adding functional groups to the surface of agricultural wastes. In addition, the hydrophobicity and mechanical strength of adsorbents are improved by esterification as well . These beneficial changes from esterification contribute to enhanced adsorption performance of agricultural wastes for application in remediation of aqueous systems. Crop straws are widely used as a feedstock for esterification treatment. For instance, soybean straw and citric acid were mixed at a solid:liquid ratio of 1:10 and reacted at 50°C for 24h and 120°C for 90min to prepare an esterified adsorbent . After modification, a strong stretching vibration at 1742 cm−1 occurred in the FTIR spectrum, indicating a successful esterification process . The -OH of cellulose reacted with citric acid to form ester linkages and imparted carboxyl groups onto the straw surface.

With regard to the adsorption mechanisms, the carboxyl groups introduced by citric acid reacted with Cu2+ via a complexation reaction. Similarly, the etherification procedure was adopted to prepare esterified rice straw using EDTA as a modifying agent. The EDTA etherification processes generated both amino groups and carboxyl groups as adsorbents . The relative peak shifts and signal strength alterations of FTIR spectrums revealed the combined actions of carboxyl, ester and amine groups of the grafted EDTA in Pb2+ binding. Additionally, some studies determined that the carboxyl esterification not only introduced more carboxyl groups on wheat straw, but also roughened the surface, thereby increasing surface area and porosity . As a result, the increased -COO− content and porous surface properties enhanced methylene blue sorption through improved ion exchange and intraparticle diffusion. The type of esterification reagent strongly affects the adsorption properties of agricultural wastes. For example, citric acid modified sesame straw fixed more methylene blue than that formed by tartaric acid modification . The contrasting effects of these two reagents were attributed to differences in their molecular structures. Citric acid possesses more carboxyl groups than tartaric acid, which resulted in generation of more adsorption sites following citric acid treatment than for tartaric acid treatment . The FTIR spectrum of the modified materials confirmed a large increase in the intensity of the C=O stretching peak resulting from citric acid treatment. Catalyst addition could further promote the esterifcation efficiency during modification. The esterification between citric acid and hydroxyl groups achieved in high efficiency using a mild catalyst in a N, N-dimethylformamide medium , NaH2PO2·H2O, as a catalyst, increased the speed of the esterification reaction and allowed for a simplified procedure compared to traditional methods without catalyst. Te catalyzed process created ester linkages within the spent grain complex and increased carboxylic acid groups on the adsorbent surface. Several studies demonstrated improved adsorption performance for pollutants following esterification of agricultural wastes . Adsorption of Cu2+ by citric acid modified soybean straw was rapid during the first 10min and reached a maximum adsorption capacity of 0.69 to 0.76mmol g−1 based on a Langmuir model . The adsorption mechanism also changed due to the increase of functional groups. The biosorption energy of citric acid modified barley straw for Cu2+ adsorption was 8.513kJ mol−1 , indicating a chemical adsorption mechanism,25 liter plant pot as opposed to a physical adsorption mechanism for the raw biomass . Similarly, Pb2+ adsorption capacity increased from 125.84mg g−1 to 293.30mg g−1 due to the formation of both ester linkages and grafting of carboxyl groups . For organic pollutants, the intensity of chemisorption was closely related to the number of functional groups. Methylene blue adsorption capacity increased from 170mg g−1 to 650mg g−1 and 280mg g−1 . The larger methylene blue adsorption capacity for the citric acid treatment was due to a larger increase of C=O in carboxyl groups, which interacted with methylene blue via complexation. In general, carboxyl and amino functional groups are the most common groups introduced onto adsorbents by esterifcation, which consequently improve adsorption performance through complexation reactions.Ethers are synthesized through etherification, whereby -OH groups on agricultural wastes are substituted by other functional groups .

Reaction of -OH groups with ethylene oxide or other epoxides is a typical etherification reaction yielding several reactive sites for further functionalization to introduce adsorption groups. Triethyleneteramine, diethylenetriamine and ethylenediamine are usually used to generate amine groups for adsorbents during the functionalization process. Generally, carboxyl, thio and amino functional groups are introduced to the biomass surfaces by the etherification process . Etherification may generate positively-charged functional groups to augment sorption sites for retention of anions, such as PO4 3−, NO3 − and SO4 2− . The interaction between epichlorohydrin and -OH groups of agricultural wastes is a common etherification process to generate new functional groups. For example, epoxy and amino groups were introduced onto raw rice straw by reaction between epichlorohydrin and trimethylamine . An FTIR peak associated with the C-N bond at 1470 cm−1 and a peak for quaternary ammonium salt at 1062 cm−1 appeared on the surface of rice straw following modification, thereby indicating generation of positively charged amino groups. This etherification process increased the total exchange capacity of the adsorbent from 0.32 to 1.64mEq g−1 and rapid adsorption of sulfate via an ion exchange mechanism. Similarly, ethylenediamine-cross-linked wheat straw was utilized to introduce amine groups for use in removing HCrO4 − and H2PO4 − from solutions . Although the BET surface area of the modified biomass decreased from 6.5 to 5.3 m2 g−1 , the modification process increased the quantity of positive charge. After modification, the zeta potential of the modified wheat straw was in the range of +39.3~−7.0mV compared with +5.2~−45.8mV for the raw wheat straw. The higher zeta potential for the modified material was attributed to the presence of -CN+, which possessed a stronger electrostatic attraction for anionic pollutants. Several studies have documented the efficacy of etherification for increasing the reactivity of agricultural wastes for retention of anionic pollutants through electrostatic interactions . Etherifcation processes are also utilized to improve the removal rate of cationic pollutants by introducing amino groups for modified adsorbents. Kong et al. introduced amino and carboxyl groups on the surface of wheat straw to investigate Cu2+ sorption behavior. They found that the introduced -NH2 groups shared their lone pair of electrons to form R-NH2Cu2+ complexes as the adsorption mechanism. Moreover, the introduced -COOH groups facilitated charge transfer to the O to attract the Cu2+, thereby further promoting Cu2+ retention. Etherification can also generate thio groups on adsorbents to attach cationic pollutants. Moreover, ethylenediamine and CS2 treatment generated S-containing functional groups on sugarcane bagasse, which played an important role in adsorbing Pb2+, Cu2+ and Zn2+ . Characterization of the etherification product indicated formation of -S=metal bonds formed through coordination bonds with the S atom in the biosorbent owing to the lone pair of S electrons sharing a bond with the metal. A summary of etherification modified agricultural wastes as adsorbents for the removal of pollutants from aqueous solution were presented in Table 4. The maximum Cu2+ sorption capacity of etherified wheat straw cellulose reached up to 130mg g−1 , which were attributed to complexation reactions of Cu2+ with the amino and carboxyl groups generated by etherification . Additionally, adding an activated bond of -CN to the cellulose -OH groups greatly improves Cd2+ adsorption performance . The Langmuir sorption model provided a better ft to the Cd2+ adsorption equilibrium data than a Freundlich model, and determined a maximum uptake of 12.73mgg−1 for modified corn stalks, compared to 3.39mg g−1 for raw corn stalks.

Soil carbon declined from 55 to 19% and microbial biomass by up to 50% for the different treatments over the 4-year period. Microbial biomass was also strongly correlated with SOC. Hence, this study provided a unique opportunity to evaluate if different microbial taxa were more sensitive to this major carbon resource shift and to determine if crop and/or management practice altered the microbial community over the relatively short time period. We used pyrosequencing of the SSU rRNA gene to determine community structure as it provides sufficient information depth so that community responses could be quantified under the contrasting soil management schemes.After four years, microbial communities in Ghanaian soil responded to the different managements with detectable changes in their diversity and composition. The overall microbial community diversity was higher for all agricultural managements than in the elephant grass eshrub dominated unmanaged plot . Bacterial groups that were responsive to particular treatments were additions to the endogenous community found in Eu. These groups are likely part of the “rare biosphere” in the Eu community but respond to the new selection provided by the new managements. Physical disturbance of the soil under these managements due to plowing, planting, and burning of fallow plants may induce more community dynamics, including resource competition. In terms of species richness, the lowest diversity was found in BF, which was likely due to very low carbon inputs. Even though fertilizer application led to the highest carbon input due to organic residue deposition , microbial diversity was relatively lower in the EfM plot, both in terms of richness and evenness. This is likely due to the higher nutrient availability, driving a less metabolically diverse r-selected community. Conversely, the PM management sequestered some carbon as woody biomass derived from high lignin content in pigeon pea. providing more aromatic residues and slower nutrient release, as well as added N from its N2-fixation capabilities. Based on these results,black plastic planting pots and supported by previous T-RFLP analysis , pigeon pea appears to be an appropriate cover crop for the fallow period in tropical agricultural systems by fostering a diverse microbial community while also maintaining SOC and supplying nitrogen. Soil microbial community structure and specific taxa distributions were found to be most affected by SOC. Sequestered carbon appeared to largely influence Actinobacteria and Acidobacteria abundance in soil.

The low-SOC BF treatment consistently exhibited the highest abundance of Actinobacteria, mostly of the subclass Rubrobacteridae. Previously isolated bacteria within this subclass, Rubrobacter and Thermoleophilum , are resistant to radiation and are found primarily in arid soil, which is consistent with the harsh exposed soil condition due to the meager summer maize crops in last two experimental years . It does not appear that all Acidobacteria groups uniformly respond to the same environmental variables, especially SOC. This is not unexpected for this very large, diverse and understudied phylum. Acidobacteria Gp4 and Gp6 were present in higher abundances in the nutrient-enriched plots than Acidobacteria Gp1 and Gp7 , even though Acidobacteria are thought to be oligotrophs. Network analysis also supported a positive correlation between SOC and modules containing Acidobacteria Gp4 and Gp6. Previously, the abundance of Acidobacteria groups was correlated to soil pH , with Acidobacteria Gp1 and Gp3 abundance largely positively correlated to acidity while Gp4, Gp5, Gp6, and Gp7 correlated to alkalinity when soils within the ranges of 4.5e8.3 were tested . Also, wheate soybean rotation was associated with the higher Acidobacteria Gp4 abundance than continuous wheat management while Gp1 abundance was the opposite . This is also explained by a difference in soil pH of different crop rotations: wheate soybean rotation and continuous wheat management . However, our soils were within pH 6e6.9 ; as such, pH does not appear to be a significant factor in this study. Our soil exhibits lower SOC than the general range of global SOC, a narrower pH range and no cold or freezing stresses. Thus, the abundance of Acidobacteria groups in our study can provide insight into understanding the ecophysiology of the Acidobacteria phylum in low SOC and near neutral pH environments. Burning of residues produces measured soil temperatures in topical soils of 200e800 ” C at 0.5 cm and 100e200 ” C at 2.5 cm depths . Soil temperatures of 120 ” C and 250 ” C have been shown to be lethal to 34e80% and 85e99%, respectively, of the microbial biomass . Although temperature was not measured in this study, the higher proportion of Bacillales, especially genera Bacillus and Sporosarcina, in the burned plots was notable. It may be due to the heat resistance of these spore-forming bacteria. Sporosarcina spp. not only tolerates high temperature, but also grows at 50 ” C .

Our core samples were taken over the top 18.5 cm so the effect of burning was probably muted by the populations at the lower depths unaffected by temperature. The fact that we could see any effect, however, suggests that burning was selective on the resulting community. Carbon is the key resource supporting most terrestrial microbial communities. Its decline due to cultivated agriculture in temperate region soils is much slower. In tropical systems, however, the continuously warmer temperatures and where moisture is suffi- cient and perhaps cultivation occurs, there is a faster loss of organic carbon. In this study the soil carbon declined by up to 55% in only 4 years. This loss plus the lack of significant annual resupply of available carbon by plants especially in years 3 and 4 of the bare fallow treatment would be expected to be a major perturbation to the microbial community, and did show a loss of 50% of the microbial biomass . We found a significant but not dramatic change in the microbial community structure, suggesting that the community as a whole is rather resistant to this even more extreme decline in its food sources.Because of the employment opportunities and economic multipliers it creates, especially during the early stages of development, agriculture has long been at the center of discussions about poverty reduction and economic development . Increasingly, so are its related up- and down-stream activities in input supply, food logistics, food processing, retail, and food services, which, together with agriculture, make up the broader agri-food system . The AFS remains a major employer, particularly in poorer countries and for the poorer segments of society . Much hope is vested in the AFS to create badly needed jobs for youth in Africa, as well as for vulnerable populations and people in lagging regions elsewhere in the world . In contrast, employment in the AFS has dropped to only 10 percent of the labor force in high income countries, where the majority of AFS jobs are now off-farm in food processing and services. There, the domestic workforce has shifted out of the AFS. New digital technologies are enabling the automation of some historically labor-intensive agricultural tasks and providing an alternative to domestic labor substitution through international migration. COVID-19 will likely reinforce these trends. Given these developments, what role will the AFS play in the future of inclusive job creation across different countries worldwide? At the early stages of development, employment in the AFS largely coincides with employment in farming.

A large share of the population lives in rural areas and engages in subsistence production. Food supply chains are short and, for the most part, local. As countries develop, however, populations urbanize and food supply chains become longer. The income elasticity of demand for food declines, agriculture’s role as employer diminishes ,drainage pot and the farm workforce becomes older, more wage-oriented, and more immigrant.1 Urban consumers, and those with rising incomes, demand foods that are more protein- and nutrient-rich, processed, and convenient to consume. This change in demand provides some scope for agriculture related job creation beyond the farm, particularly in food processing and services. While these changes occur, jobs on the farm typically become more remunerative and competitive with jobs off the farm even though they dramatically shrink in terms of share and number.2 These dynamics, driven importantly by food demand behavior, have been observed across countries throughout history. They are broadly known as the structural transformation and the agricultural/dietary transformation . Often, these transformations are accompanied by deeply wrought societal change in response to growing rural-urban income divides and ineffective policy responses, including agricultural protectionism, especially when investment in rural public goods and inclusive food value chain development lags behind . Technological revolutions further shape these dynamics . Examples include steam power, railways and tractors in the 19th century, and electricity and cold storage in the 20th century. The current century is witnessing a rapidly unfolding digital revolution , with another revolution in energy just around the corner . These technological advancements of the 21st century and the associated business and product innovations are affecting structural and agricultural transformations across the globe. They have the potential to profoundly alter the global organization of the food system, as well as labor and skill demands. They dramatically reduce transaction costs in input and output markets, change economies of scale, and modify the optimal capital/labor mix in agricultural production, processing, and marketing. Because some agricultural tasks are arguably more automatable than those in industry and services , automation could accelerate the exit of labor out of agriculture in developing countries and transform farms and food processing firms in the developed world. A future with robots in the fields and packing plants, together with technology-savvy farm workers to complement new technological solutions in specific commodities and tasks, already is taking shape. Solar driven water pumps , cold storage, and agro-processing equipment are also beginning to spread in rural India and East Africa, accelerating the transition away from subsistence production . Historically, during this process of structural and agricultural transformation, societies typically evolved from having a surplus to a shortage of domestic farm labor. Inefficient land markets and sluggish food value chain development slowed farm consolidation and diversification, and social protection for the self employed remained limited.

As a result, farm incomes have struggled to keep up with more secure and faster-growing incomes off the farm. Domestic workers shifted from the primary sector to the secondary and tertiary. More often than not, in developed countries farm labor shortages have been filled largely by foreign agricultural wage workers, especially for difficult-to-automate tasks like harvesting fresh fruits and vegetables. Migrant-sending households in low-income countries benefited through remittances. However, with anti-immigration sentiments flying high in migrant-destination countries, the structural transformation unfolding in migrant-source countries, and technology increasingly offering alternatives to hired labor everywhere, opportunities to close income gaps across countries through legal farm labor migration may be narrowing . The shift in policy dialogue away from immigration solutions to farm labor problems coexists with a bifurcating global demographic. Many developing countries, especially in Sub-Saharan Africa, struggle to provide employment for their young, rapidly-expanding populations, presenting a missed opportunity for development from the so-called “demographic dividend” , including through international migration. Agricultural trade is similarly challenged in its role to help address global imbalances in farm labor, partly because of its purported contribution to global warming. The domestic and global forces of structural transformation and food demand behavior, the new technological revolution and associated business innovation, and the deceleration of agricultural trade and labor migration provide much of the socioeconomic backdrop against which the future of work in the AFS unfolds across countries. These transformations are further affected by the recent COVID-19 pandemic. It already has set back income growth . In the long run, the pandemic will reinforce existing trends in AFS automation and digitization and decrease reliance upon agricultural labor migration and trade, especially in the developed world. The pandemic has also exposed vulnerabilities in supply chains, as some countries experienced difficulty securing supplies of strategic goods and risks ushering in a new wave of protectionism .How countries address these, and related, challenges will shape the extent to which the AFS can continue its historically crucial role in reducing poverty and fostering shared prosperity by raising smallholder incomes and creating employment opportunities for young, expanding work forces. We argue that a policy and business environment supportive of inclusive agricultural value chain development will be a critical component of the solution. Adequate competition policies to address the challenge of rising power concentration within the AFS need to be part of the solution, as does the provision of broad access to digital infrastructure.

Snakins isolated from Solanum tuberosumare cysteine-rich peptides roughly 6.9 kDA in size and the snakins isolated from potato tubers is effective at suppressing both fungal and bacterial growth at concentrations lower than 10 μM. Transgenic potato plants overexpressing the StSN1 gene exhibited reduced symptoms of R. solani infections and higher survival rates compared to the wild type plants . Additionally, StSN1 has been shown to be effective in vitro against B. cinerea and several Fusarium species.However, snakins have been rarely expressed successfully from microbial hosts, often with low yield and insolubility, which hinders in-depth mechanistic characterization of its action towards pathogenic fungi . Another promising group of AFPs are the puroindolines, which are small, amphipathic tryptophan-rich proteins about 13 kDA in size and found only in wheat . They are known to inhibit the growth of pathogenic bacteria and fungi with low mammalian toxicity, likely through strong binding with microbial membranes and therefore perturbing the membrane integrity. These proteins are believed to protect seeds from fungal attacks during seed development and germination. There are two major puroindolines, Puroindoline A and B. When the pin genes are over expressed in transgenic rice, rice displayed significantly enhanced resistance to rice blast caused by Magnaporthe grisea and a reduction in symptoms due to Rhizoctonia solani infections . Purified PINA and PINB proteins from wheat were able to inhibit the growth of a variety of pathogenic fungi, including Alternaria brassicola, Ascochyta pisi, F. culmorum, F. graminearum, Magnaporthe girsea, R. solani, and Verticillium dahlia. PINA and PINB are stable over a broad range of temperature and pH. PINs have been heterologously produced in Pichia pastoris with a titer up to 14 mg/L taking advantage of puroindoline’s solubility in the detergent Triton X-114 . These various AFPs discussed highlight the potential of using AFPs as anti-fungal agents for agricultural purposes. In the past decade,vertical tower for strawberries there has been an increase in interest towards proteins containing domain of unknown function for their capability in fighting plant pathogens and especially fungi .

DUF26 is a cysteine rich domain with a conserved C-X8-C-X2-C motif. DUF26-containing proteins are a large, land plant-specific protein family and characteristic of embryophytes . Similarities with fungal lectins suggests DUF26-containing proteins constitute a group of plant carbohydrate-binding proteins able to recognize specific fungal sugar motifs. There are three groups of DUF26-containing proteins: the cysteinerich receptor-like secreted proteins , cysteine-rich receptorlike kinase and plasmodesmata-localized proteins . The three DUF26-containing protein groups were all previously associated with anti-fungal activities. Nevertheless, only CRRSPs remain as good candidates for biotechnological application since CRKs and PDLPs contain transmembrane domains and localize to the membranes. CRRSPs contain a signal peptide followed by one or more DUF26 domains, separated by a variable region. The most well-known CRRSP is Ginkbilobin2 , which was isolated from seeds of Ginkgo biloba and able to inhibit the growth of F. oxysporum, T. reesei, and C. albicans. This anti-fungal activity is likely due to the binding of DUF26 domain with sugar moieties on the fungal cell wall . For instance, Gnk2 interacts specifically with mannan, a yeast cell wall polysaccharide, and mannose, a building block of mannan, by strictly recognizing the hydroxy group at the C4 position of the monosaccharide. Consistently, two maize CRRSPs have been characterized to interact directly with the hyphal surface of Ustilago maydis, and the activity can be rendered by Rsp3, a U. maydis effector covering its surface . In addition to direct binding with fungal cell walls, DUF26- containing proteins from CRRSP family also protect plants using indirect mechanisms. CRR1, a secreted apoplastic protein from cotton, and composed of two Cys-rich DUF26 motifs, interacts and protects the anti-fungal apoplastic chitinase 28 from cleavage by VdSSEP1, a pathogen related protease. Importantly, over expressing CRR1 in heterologous plants such as Arabidopsis thaliana and Nicothiana tabacum improved plant resistance to B. cinerea and P. parasitica, respectively. Thus, CRR1 could be a good candidate as a co-anti-fungal agent and simultaneous exogenous application of CRR1 and chitinases should be evaluated. Another CRRSP of interest is the recently reported CBM1-interacting protein in rice.

Pathogenetic fungi generally use cell wall degrading enzymes to destruct plant cell walls, and many CWDEs use carbohydrate binding modules to facilitate the access to plant polysaccharides to advance the infection process . OsCBMIP can specifically bind to CBM of several CBM-containing CWDEs including the xylanase MoCel10A of the blast fungus pathogen Magnaporthe oryzae and slow down the infection progress. Interestingly, OsCBMIP cannot inhibit the growth of M. oryzae and F. oxysporum in vitro, and this further indicates that OsCBMIP slows down the infection of pathogenetic fungi through indirect mechanism, here specially, through inhibiting CBM-containing CWDEs. In another study, a transcriptomic analysis of wheat after Bipolaris sorokiniana or Rhizoctania cerealis infection reported the induction of a cysteine-rich protein , TaCRR. When heterologously expressed, this DUF26-containing protein showed a clear anti-fungal activity. Besides, it was found that silencing TaCRR gene in wheat significantly decreased the expression of pathogenesis-related genes such as β-1,3-glucanase, defensin or chitinases. Owing to their apoplastic localization and direct or indirect anti-fungal activities, DUF26-containing proteins from the CRRSP class remain as attractive candidates for the future development of anti-fungal agents. Polygalacturonase inhibiting proteins are a family of leucine rich repeat proteins found in plant cell walls whose primary role is to inhibit polygalacturonases , enzymes secreted by insects and fungal pathogens that degrade the plant cell walls and leave it vulnerable for infection . Through competitive or noncompetitive inhibition, PGIPs slow the hydrolysis process of PGs . Presently, numerous studies show that overexpression of PGIPs in transgenic plants leads to increased fungal resistance. The best-documented PGIP is PGIP2 from Phaseolus vulgaris , the common bean. PvPGIP2 has been successfully expressed in transgenic plants, resulting in increased resistance to fungal infections against Alternaria citri, Aspergillus flavus, A. niger, B. cinerea, Claviceps purpurea, and F. graminearum. Similarly, expression of PGIP3 from soybeans in tobacco has been shown to inhibit the growth of pathogenic Sclerotinia sclerotiorum, Fusarium moniliforme, B. aclada, A. niger, Collectotrichum acutatum, and F. graminearum; and expressing PGIP2 from lima beans in tobacco also delayed growth of Collectrichum lupini, B. cinerea, F. moniliforme, and A. niger.

Recently, it is also found that truncated PvPGIP2 with only the optimal docking area retains similar level of inhibitory activities towards PGs from A. niger and B. cinerea to the full-length PvPGIP2 . Yeast strains secreting full-length or truncated PvPGIP2 with the Ost 1 signal peptide were also able to reduce fungal growth and delay sporulation by 1–2 days . Although the function of PGIPs when applied exogenously on plants has not been reported, this group of proteins is still considered as a promising candidate to be developed into an eco-friendly fungal control agent. Albumins are a major class of water soluble, seed storage proteins that are used as a source of nutrients for plants during germination. Among them, 2S albumins have anti-fungal capabilities, in addition to a variety of activities including anti-cancer, anti-fungal, anti-bacterial, and serine-protease inhibiting properties . These small storage proteins are present in both monocotyledonous and dicotyledonous plant seeds and typically have a disulfide bridge linking two different subunits,container vertical farming which are typically between 3 kDA and 10 kDA in size. For example, pumpkin 2S albumin is thermal-stable at up to 90 ◦C, and exhibits inhibitory activity against the fungal pathogen F. oxysporum. Similarly, a crude extract of peanut containing 2S albumin was found to inhibit growth of A. flavus; the 2S albumin ortholog from passionfruit could also inhibit the fungal pathogens T. harizanum and F. oxysporum, C. musae, and C. lindemuthianum; and the 2S albumin ortholog from Putranjiva roxburghiicould inhibit the growth of F. oxysporum, Phanerochaete chrysosporium, C. albicans, Aspergillus fumigatus, and A. flavus. In addition, putrin is stable at up to 50 ◦C and within a pH range from 6 – 8. On the other hand, 2S albumin from white sesame seeds, oriental mustard, and Brazil nuts can bind to IgE sera, which may trigger an allergic response in humans. Thus, before 2S albumin can be utilized as an exogenously applied anti-fungal agent, we need to either engineer the protein to eliminate or reduce the allergenicity or modify the application in a manner that avoids either extensive contact or consumption. The fresh market berry industry in Santa Cruz and Monterey counties is an excellent example of transformation in the business of agriculture over the last 50 years. Located along the Central Coast of California, the two counties span the fertile Pajaro and Salinas valleys, and are well known for their amenable climate and production conditions, their diverse crop mix and grower demographics, and their developed agricultural infrastructure and support industries. The majority of the berry sector is comprised of strawberries , raspberries and blackberries , with blueberries and other miscellaneous berries produced on a much more limited basis. Substantial research-based literature and historical information is available for Central Coast strawberries; however, despite the area’s move towards greater production of raspberries and blackberries, less information exists for these crops.

We seek here to provide a more complete portrayal and historical context for the berry industry in the Santa Cruz and Monterey area, which is the origin of the berry industry in California. While the berry industry has been very successful in recent decades, it now faces new challenges, such as invasive pests and the phaseout of the soil fumigant methyl bromide. This article draws on previous and more recent research to discuss some of the influences that have contributed to the berry industry’s dramatic expansion in Santa Cruz and Monterey counties, including selected innovations in agricultural practices and heightened consumer demand. Berry industry growth During the 1960s and 1970s, the number of acres planted to berries, tons produced and value of production fluctuated. The fluctuations can be partly explained by farm management: in the past growers often rotated berry and vegetable crops to assist with soil and pest management, thereby influencing these statistics. However, annual crop reports from the county agricultural commissioners show that since the 1980s, berries have become increasingly important to each county’s overall value of production, and by 2014 accounted for 64% and 17% of the total value of all agricultural products in Santa Cruz and Monterey counties, respectively . The industry’s growth can be explained by a shift of some acreage out of tree fruits and field crops , among others, into berries, and by additional acreage put into agricultural production. Strawberries are the undisputed leader in the berry sector and in 2014 represented 58% and 94% of the value of all berry production in Santa Cruz and Monterey counties, respectively , and 50% and 93% of all berry acreage . Table 2 documents the remarkable expansion of the strawberry industry over time in both counties with respect to acreage, tons produced and value of production. Between 1960 and 2014, acreage more than tripled and production increased tenfold. The value of production, in real dollars, increased by 424% in Monterey County and by 593% in Santa Cruz County, reaching an astonishing combined value of nearly $1 billion in both 2010 and 2014. The gains in all statistical categories in Monterey County were enabled in part by an expansion of production into the southern reaches of the county where more and larger blocks of farmland are available, and where land rents are lower than in Santa Cruz and northern Monterey counties. However, from 2010 to 2014 Monterey County’s tonnage and production values declined, possibly because the area has recently experienced a shortage of labor to harvest fresh market crops. Tonnage was also lower in Santa Cruz County, but production values increased. This may be because of the county’s greater emphasis on local agriculture, organic production and direct market sales, which are often associated with higher crop values. For raspberries, the acreage, tons produced and value of production grew steadily and most strikingly in Santa Cruz County , where production conditions for caneberries are optimal. For example, caneberry fields in Santa Cruz County are situated in areas that have well-drained soils and are protected from damaging winds. Also, fields are planted to take advantage of the growth and yield gains associated with southern exposures. Moreover, field-to-cooler travel distances are shorter in Santa Cruz County, which is critical for safeguarding the quality and marketability of these highly perishable crops.

The lack of location-specific information for both model input and model constraints thus is the largest uncertainty in quantifying field-level carbon outcomes . For any technology used for carbon outcome quantification, there is a trade off between cost and accuracy . Although no clear criterion has been established so far to accept or reject a technology, for any quantification technology to be scalable, its per-acre operational cost must be meaningfully lower or significantly lower than the expected monetized carbon values from adopting climate-smart practices. In the current U.S. agriculture carbon market with a carbon price of roughly US $20/t CO2e, for example, this criterion, based on the DOE ARPA-E estimation , means costs should be significantly lower than $10/acre/year for soil carbon and $50/acre/year for N2O quantification for large-scale deployment, including installation, calibration, operation, and hardware lifetime and at the same time, the technology should be able to achieve less than 20% error at the field level . No single existing technology can meet both of these expectations. Instead, we propose that a more viable path for quantification of field-level carbon outcomes in agricultural soils is through an integration of sampling, sensing, and modeling, defined as the “System-of-Systems” solution. The “System-of-Systems” concept means that the complex problem of quantifying agroecosystem carbon outcomes cannot be solved by using a single sensor or a model alone, but only can be solved by effectively integrating various approaches . Such a “System-of-Systems” solution should simultaneously comprise the following features : scalable collection of ground truth data and cross-scale sensing of E, M, and C at the local field level; advanced modeling with necessary processes to support the quantification of carbon outcomes; systematic Model-Data Fusion , i.e. robust and efficient methods to integrate sensing data and models at each local farmland level; high computation efficiency and AI to scale to millions of individual fields with low cost; robust and multi-tier validation systems and infrastructures to test model/solution’s scalability, defined as the ability of a solution to perform robustly with accepted accuracy on all targeted fields.

Thus the “System-of-Systems” solution is a holistic framework including multiple sub-systems for sensing, monitoring, modeling, and model-data fusion,hydroponi bucket targeting to assure field-level accuracy, scalability, and cost-effectiveness. The “System-of-Systems” approach is so far the only pathway to implement the mass-balance approach to quantify SOC changes, which requires various localized observations and the integration of observations/data with models to accurately estimate each term in the massbalance equation and achieve the field-level accuracy. Compared with existing approaches , there are several advantages of using the mass-balance approach to quantify the change of SOC. First, all of the carbon budget terms are measurable, although some being costly, and can be used to verify model accuracy and provide a basis for confidence. Second, all the carbon budget terms can be measured and verified at relatively short time scales, i.e. from sub-hourly scale to annual time scale , which enables the quantification of annual change of SOC. In contrast, soil sampling is generally not able to detect annual changes, as the uncertainty of soil sampling is usually much larger than the annual change of SOC. Third, those carbon budget terms for calculating the carbon input to soil can be estimated using advanced remote sensing technologies , which offers an efficient and scalable way to achieve the field-level observational constraints in a large region due to the ubiquitous coverage of remote sensing technologies. Fourth, the carbon mass balance approach provides a holistic picture of the overall carbon budget of farmland soils, which enables a mechanistic understanding of differential impacts of management practices on SOC from field to field and from year to year, thereby could help farmers to improve their management practices along with the changing climate. Scalably sensing/estimating local information of E, M, and C at the field level is the first step of a “System-of-Systems” solution, which involves two seemingly different but inherently connected tasks: ground truth collection, and cross-scale sensing. Ground truth here is broadly defined as information that is collected on the ground to train, constrain or validate models. Agricultural ground truth is scarce and expensive to collect.

For example, collecting carbon flux data requires eddy-covariance flux towers, which are generally costly to set up and operate. However, we also have to face the reality that even with low-cost sensing technology or crowd sourcing efforts, one cannot collect ground truth for every field. Instead, we propose to develop “cross-scale sensing” approaches, especially those enabled by remote sensing, to scale-up “ground truth” collection to large scales. Cross-scale sensing can be demonstrated by the most recent development of deriving field-level photosynthesis information. Photosynthesis is the only term for land carbon input and also the largest carbon budget term . Ecosystem photosynthesis is the primary driver for crop litter and thus significantly contributes to the long-term change in SOC, as demonstrated in Section 2.3. Correctly quantifying photosynthesis at the field level puts significant constraint and reduces uncertainty on simulated crop carbon dynamics, crop litter and soil carbon dynamics . A recent breakthrough in the remote sensing of photosynthesis was made possible by full integration of leaf level chamber/sensor measurements, canopy-level hyperspectral sensing , and regional-scale mapping through satellite fusion data . The cross-scale sensing here is guided by the domain knowledge of plant physiology, radiative transfer modeling, and hyperspectral theories; ground truth data – in particular, leaf-level samples and eddy-covariance flux tower data – are extensively used in the model development stage, but once the translation from ground-truth data to satellite-scale signals can be robustly developed, satellite fusion data can expand the photosynthesis information for every single field every day since 2000 to present . Another advance in cross-scale sensing is the use of intermediate sensing to augment traditional ground truth collection, and enable the scaling from leaf-level or plot-level ground measurements to coarse satellite pixel size – a classic problem in the area of remote sensing. A typical example is the use of airborne hyperspectral imaging . Hyperspectral imaging can provide estimates of certain soil and plant traits with high accuracy , although its application for scalable mapping has been limited by its high cost.

A novel use of AHI is to treat AHI data as an intermediate bridge between ground truth collection and satellite scale-up. A general procedure is to first develop robust methods to translate AHI signals with targeted estimates based on data from intensive lab and field experiments; and then to use AHI as a strategic sampler to selectively “sample” over space and time, serving as a bridge from granular resolution of ground truth to large satellite pixels; and finally, to use satellite data overlaid with the AHI sampled area to translate satellite multi-spectral signals along with environmental variables into plant and soil trait estimation, thus deriving targeted E, M, C variables ubiquitously using satellite data. Though similar approaches have achieved success in mapping forests canopy bio-geochemistry , they have rarely been used in agroecosystems. Once advanced and automated pipelines are established to conduct AHI collection and data processing , AHI can be applied to estimate crop canopy nitrogen content, cover crop biomass, and crop residue fraction and tillage practices. Fig. 7 demonstrates how AHI is used to scale up the estimation of crop residue fraction and tillage intensity at the regional scale. Other sensing approaches, such as mobile vehicle sensing , IoT sensing network and robotics , could also achieve a similar function to augment ground truth collection and enable satellite scaling-up to regional scales. Table 1 provides a non-inclusive list of different critical E, M, C variables that currently have been estimated using cross-scale sensing technologies. Have sufficient and necessary processes represented. Coupled carbon-nutrient-water-energy cycling over farmland is the foundation for field-level carbon outcome quantification,stackable planters thus models should include a sufficient number of mechanistic pathways that clearly track the input, output and storage of water, carbon, nutrient and energy in crop lands under the interference of agricultural management. For the plant component, simulating the responses of crop carbon uptake and water use to different abiotic and biotic stresses is necessary as they largely determine the crop production and carbon input to the soil. From this perspective, proper representation of canopy energy balance, stomatal conductance, uptake and transport of water and nutrients from soil to canopy are needed to mechanistically simulate the crop carbon and nutrient uptake and crop water use . Many of the existing process-based models may lack critical processes or use over-simplified processes to model specific carbon outcomes. One obvious example, following our prior discussion on the importance of the holistic carbon budget of agroecosystems, is that most existing process-based models lack sufficient mechanisms that can model plant carbon processes as emergent phenomenon , resulting in significant errors when quantifying the downstream ΔSOC. For example, lack of explicit modeling of photosynthesis , plant stomatal responses to environmental stresses , and reproductive processes for yield can cause huge uncertainty of the modeled carbon input to the soil pools, contributing significant error to the simulated ΔSOC. For the below ground part, soil temperature, water, oxygen, and pH dynamics, bio-geochemical reactions related to carbon, nitrogen and phosphorus cycling, microbial activities and their regulation on SOM formation and stabilization as well as GHG emissions are core processes that need to be simulated. For example, recent studies identified two distinct pathways of SOM stabilization from litter decomposition, i.e. the DOM-microbial pathway in the early stage of decomposition, and the physical transfer pathway in the final stage of decomposition .

This work emphasized the importance of dissolved organic matter and microbial activities, and necromass in stabilizing SOM . Having those mechanisms and their interactions with related environmental drivers well represented in the soil carbon models is essential to accurately simulate the dynamics of SOC and its physical fractionations. Besides these biophysical and bio-geochemical processes, representing the farming management practices and their impacts on coupled carbon nutrient-water-energy cycling over farmland is critically needed to quantify the carbon outcomes. Neverthless, there should be a good balance between model complexity and practicality. Any model used for operational carbon outcomes quantification should have necessary complexity and processes, and new theoretical advances in science should be ultimately incorporated into existing models to improve representations of relevant processes. However, we also need to acknowledge that models with new mechanistic representations are not always better than simpler models in practice, especially when there is not enough data to constrain those new mechanistic representations. When evaluating the appropriate model structures for agricultural carbon outcomes, we should focus on two fundamental questions: Is a specific process indispensable for simulating the specific outcome and also achieving the desired accuracy? Is there sufficient data to parameterize that specific process at both field and regional scales? If the answer to either question is no, then including the new process may not necessarily benefit the quantification of carbon outcome for now. Maximum use of mechanistic process representation. To simulate biogeochemical and biogeophysical processes, many existing models use multiplication factors , law of the minimum , and empirically-derived response functions , all of which are ad hoc by nature. One consequence of these non-mechanistic modeling approaches is that different researchers applying the same method to a given process will obtain different mathematical representations, which then lead to a loose foundation to implement that particular process in these models . Moreover, non-mechanistic representation which lacks support from physical laws also limits the generality and scalability of the model simulations, especially when a model is used to extrapolate beyond the environmental and management conditions under which the model is previously developed or calibrated. For example, many models use the empirically-derived soil water stress functions to depict the down-regulation of crop carbon uptake and water use under water stress conditions, which causes inconsistencies and discrepancies in multi-model intercomparison simulations . A more mechanistic way to account for crop soil water stress would be to explicitly represent the plant-hydraulic-stomatal-photosynthetic coordination from soils to plant, and to atmosphere . Similarly, most models formulate soil carbon decomposition rate by assuming different controlling factors independently and multiplicatively scale the decomposition rate ; in reality, these factors are interacting and intertwined following specific mechanistic pathways to lead to decomposition rate, but very few existing models include such interactions and mechanistic pathways . Another example is how the impacts of different tillage practices are represented on soil physical and biogeochemical processes.

In the northern Peloponnese, currants were grown in Patras, in Vostizza , and in the village of Sikionas, just West of Corinth. Currants also spread to the southern coast of Aetolia in towns along the gulf, including Lepanto , Anatolikon , and Messolonghi. From these locations, currants were shipped to the port of Patras, which became the bulking center for currants grown in Ottoman territory before their journey westward.Despite the continuing cultivation of currants in Ottoman Greece in the sixteenth and seventeenth centuries, most currants were grown on the Venetian Ionian Islands during this time. The English traveler to the Ionian Islands Sir George Wheler wrote in the late seventeenth century that Zakynthos produced enough currants annually to fill five or six cargoes, and Kephalonia produced enough to fill three or four. At the same time, all the currant-growing regions around the Gulf of Corinth in Ottoman Greece—Anatolikon, Messolonghi, Patras, and Lepanto—together only produced enough to fill a single cargo.This continued throughout the eighteenth century and well into the nineteenth century, even as currant cultivation abated substantially on Zakynthos and Kephalonia and intensified somewhat in Ottoman Greece. In the eighteenth century, currants circulated through the early modern trade networks that connected the major trading hubs of the Mediterranean, including Venice, Trieste, Livorno, Smyrna, and Constantinople. The primary market was England, but they were also destined for consumption in Holland and elsewhere in Europe. By the end of the eighteenth century, there were six million Venetian liters of currants being exported from the Peloponnese, mainly from Patras.On the eve of the Greek Revolution, currant cultivation was growing, but currants remained the product of isolated zones of specialization around the Gulf of Corinth and on the Ionian Islands. The currant-growing places were not yet united into a region—they remained small islands surrounded by a sea of diverse cultivation. First, the demand for currants in Britain,livestock fodder system the main currant-importing country, increased due to changing consumption habits.

This was just the latest development in a longer process. In the eighteenth century in Britain, the growing middling and trading classes had adopted new consumption habits. Demand for luxury items was previously limited to the old elite, but with the expansion of British trade and growing prosperity, there was an increase in demand for luxury items and non-essential food commodities from faraway places such as tea and sugar and the porcelain and silver with which to consume them.The Industrial Revolution in Britain in the late eighteenth and early nineteenth centuries expanded this consumer class even more and increased demand for these commodities. Rituals were created to consume these commodities. For example, breakfast and tea-drinking were both new rituals that were introduced in Britain in the eighteenth century. These customs coincided with the introduction of hot beverages such as coffee, chocolate, and tea and the ceramic, silver, and steel commodities used to consume them. By the middle of the eighteenth century, it was customary among middling and trading groups to consume a breakfast of bread and tea.One of the commodities that experienced a rise in demand was puddings, or sweet desserts made with sugar and dried fruit—particularly Greek currants. As described above, the market for currants in England to be consumed in puddings goes back to the fourteenth century or earlier, but because of new consumption patterns, around the middle of the nineteenth century, this market began to grow at a much faster rate. By the middle of the century, currants were the main export of the Peloponnese and of all of the Kingdom of Greece, and the UK was their principle market.The second half of the nineteenth century marks the period that Nikos Bakounakis calls the “age of pudding” in Victorian Britain.38 Pudding consumption rose in Britain among the lower and middling classes, and dried fruits were an essential ingredient in these puddings.The publication of Charles Dickens’s A Christmas Carol in 1843 popularized the holiday ritual of serving Christmas pudding made with dried fruit and adorned with a sprig of holly. Christmas pudding became a mainstay of the season, and other puddings became popular as year-round favorites.

The recipe for spotted dick, for example, which seems to date to an 1849 cookbook marketed to middle-class British housewives, calls for “Smyrna raisins” or sultanas to create the “spots.”Puddings became a sign of abundance and of the happiness of the bourgeois family— Greek currants became an essential ingredient in the aspirations of the upwardly mobile British population. Pudding consumption rose in Britain among the lower and middle classes, and Greek currants benefitted from this general trend. During the period from 1846 to 1876, the consumption of sugar and currants rose dramatically. Annual sugar consumption in England was 14 lbs. per person in 1846, but it grew to 60 lbs. in 1876. Currant consumption rose to a similar degree: total currant consumption in England was 14,000 tons in 1844, and it rose to 46,000 tons in 1874. Moreover, as the demand for dried fruit increased, currants also captured a greater relative share of this market. Currants displaced other types of raisins in London and Liverpool. In the years 1831 to 1840, 48% of the raisins consumed in these cities were currants. This number grew to 66% from 1860 to 1869.In the 1870s, 55% to 75% of Greek currants were being exported to Britain to meet this growing demand.As a French traveler to Greece wrote in the middle of the nineteenth century, “If Greece were to cease to produce these precious little black grains, there would be no more plum-puddings, nor plum-cakes, nor any of those dainties of which plums or currants are the foundation…. England would have been deprived of the purest of her pleasures, and Greece of the most certain of her revenues.”44 The demand from Britain was also promoted by greater access to the currant trade in the Peloponnese in the nineteenth century. During this time, Patras rose in importance to become the main port of the Peloponnese and one of the three main ports in the Kingdom of Greece alongside Piraeus and Hermoupolis. In the eighteenth century, Patras was an important regional port that served as a “bulking” or collecting center for the Gulf of Corinth and Elis. Smaller ports such as Vostizza and Lepanto sent their cargoes to Patras to be collected before being sent on to European ports to the West.

The other major ports on the Peloponnese—Navarino, Methoni, Coroni, and Nafplion—shared the rest of the peninsula’s trade. The French Revolution was a turning point for Patras, when the French lost their control over trade in the eastern Mediterranean. For the duration of the French Revolutionary period , Greek merchants dominated trade in the eastern Mediterranean more than any other group. As a result, the French ports such as Coroni declined. Moreover, with the implementation of the Continental System, the British turned to the Eastern Mediterranean for sources of commodities and for markets for their manufactured goods. Consequently, Patras enjoyed a greater relative share of the peninsula’s trade and increasing trade with Britain. During the French Revolutionary period,Patras handled 30% of all Peloponnesian exports to Western Europe, and the rest was divided among the peninsula’s other ports.46 After the Napoleonic Wars, the English displaced the French in the Eastern Mediterranean. The Italian ports declined, but Patras continued to grow through closer connection to British ports in the Ionian Islands and Malta. From 1815 to 1820, Patras’s relative share of the peninsula’s trade with the West suddenly doubled from 30% to 60%. Due to the disruptions caused by the French Revolution, Patras emerged as the dominant Peloponnesian port for trade with Western Europe and the eastern Mediterranean.During the Greek War of Independence, Patras was completely destroyed, the population left, and the land was not cultivated. The war was a violent break with the past, but Patras and its vineyards were able to recover quickly. The destruction left Patras as a tabula rasa. Under the influence of British demand for currants,hydroponic nft gully the city was remade into a port-city with its orientation shifted to the sea. Before the war, the center of  Patras was perched on a hillside, and the city was oriented inward toward its hinterland. After the war was over, the old town on the hillside was rebuilt, but a new city was also built on the coast beside the old city on land that was previously occupied by vineyards .The engineer Stamati Voulgaris who planned the reconstruction of the city moved the demographic and economic center of the city from the hills to the sea and made plans for a new port. Patras after the Greek Revolution was therefore a new city with a “double” landscape: the sea and the plains on the one hand, and the hills on the other.The newly rebuilt Patras sent most of its exports to Britain and its territories in the eastern Mediterranean. Patras continued to ship to the Italian ports, but the percentage of total exports from Patras that were bound for London, the Ionian Islands, and Malta reached 73%.Patras also began receiving imports directly from European ports. Before the revolution, Patras received European commodities after they had stopped first in a larger Ottoman port such as Smyrna.

As a part of the newly independent Kingdom of Greece, Patras received cargoes of textiles sent from British ports in the Ionian Islands and Malta. Patras also imported other manufactured goods and food commodities such as sugar, coffee, and pepper.51 By the 1830s, therefore, the currant trade and Greek trade with Britain were both concentrated in the port of Patras. The technological innovations of the Second Industrial Revolution lowered the speed and costs of transit, promoting the continuing integration of Greek agricultural production with Western markets. Most significantly, improved steam ship transport in the second half of the nineteenth century meant that Patras no longer needed to trade with Britain through the ports in its Mediterranean colonies but could trade directly with British ports. By the middle of the century, merchants had opened steam ship lines to carry currants directly from Patras to London, Liverpool, Falmouth, Newcastle, and Southampton, and Patras also began importing directly from British ports. Patras continued to trade with Malta and the Ionian Islands, but now there was a direct connection as well.Steam ship transport also deepened the currant growing region’s connections to North America. The United States had begun importing Greek currants as early as 1835 due to the efforts of the Chian merchants Andreas and Pantellis Phakiris and their merchant house based in Patras.London had a near monopoly on shipping currants to the US and Canada at first, but by the end of the nineteenth century, steam ships were leaving Patras bound directly for North American ports.54 In fact, currants were the sole reason for trade between Greece and the US. Until the very end of the nineteenth century, currants made up 90– 100% of Greek exports to the US.A technical innovation in the practice of currant cultivation in the Peloponnese may have also played a role in the spread of currant cultivation further to the west and the south in the second half of the nineteenth century. This was a technique called “girdling” or “ring-cutting” . Ring-cutting involved removing a thin strip of bark in a ring around the base of the vine, about 2–3 cm. wide. Ring-cutting was done in mid-May at the appearance of the first growth on the currant vines. Ring-cutting was strenuous work performed by skilled laborers called harakotes. If done right, ring-cutting caused the fruit to grow larger, but there was plenty of room for error, and the stakes were high. If the faltseta, or pruning knife, cut too deep, the vine would die, but if it did not cut deep enough, the cut would be ineffective. The harakotis also had to determine the appropriate width of the cut based on the quality of the soil and the age and strength of the vine. Weaker vines and less fertile soil required a narrower cut, and hardier vines and more fertile soil required a wider cut. Moreover, the task had to be completed within ten days, “as otherwise the ripening of grapes would not be uniform and problems would arise at harvest-time.”Because it was physically taxing, time consuming, and required special skill, ring-cutting was highly paid work.Ring-cutting was introduced in the Peloponnese in 1848 when the technique was first applied by workers who came to the peninsula from Zakynthos.