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The effect size in each case represents the difference compared to the water control treatment group

MS-DIAL features were clustered by applying a Pearson correlation, with a minimum correlation of 0.8 and maximum p value of 0.05, retaining two features per cluster according to most intense and the most connected peak filters . Selected peaks were imported into MS-FINDER for annotation . Mass tolerance for MS1 and MS2 were set to 5 and 15 ppm respectively, the relative abundance cut off set at 1% and the formula finder was configured to use C, H, O, N, P, and S atoms. FooDB, PlantCyc, ChEBI, NPA, NANPDB, COCONUT, KNApSAcK, PubChem, and UNPD were used as local databases. During the final merge step in MS-CleanR, the best annotation for each peak was based on MS-FINDER scores. The normalized annotated peaks list produced by MS-CleanR was used for the final statistical analyses in R. A partial least squares supervised model of the complete log-transformed and Pareto-scaled dataset was done using the ropls package , with the three treatment groups as the response variables. Ellipses were drawn around treatments using stat_ellipsebased on a 95% confidence level. This distance type considers the correlation between variables and the ellipses are created around the centroid data point. Heatmaps were created using the log-transformed data within the ComplexHeatmap package in R , with hierarchical clustering according to the complete-linkage method and Euclidean distance measure across columns and rows, displayed as dendrograms.Pairwise multivariate analysis was performed across all time points between ANE and H2O, and between AA and H2O, using an orthogonal projections to latent structures discriminant analysis . OPLS-DA models were generated using the ropls package, macetas plastico cuadradas with the predictive components set to 1 and orthogonal components to 7. S-plots were generated following sample sum normalization and Pareto scaling via calculation of p1 and pcorr1 of the OPLS-DA scores using the muma package source code within R.

Chemical class enrichment analysis was achieved using ChemRICH for each two-treatment comparison at each time point within R using the source code . A student’s t-test of the signal was conducted to generate p values and effect size. Previous transcriptomic work revealed a high level of congruency in differentially expressed genes in AA- and ANE-treated tomato seedlings compared to H2O-treated controls . To further this line of investigation, the metabolomic profiles of AA- and ANEroot-treated plants were compared to H2O after 24-, 48-, 72-, and 96-hours exposure to their respective treatments. Locally-treated roots and distal leaves were harvested, flash frozen, extracted for metabolites, and subsequently analyzed via LC-MS, which with underivatized samples primarily captures the nonvolatile metabolome . Partial least squares score plots of tomato root tissue revealed distinct clustering by treatment irrespective of time point . No overlap was observed in the 95% confidence ellipses for any treatment group. Likewise, heatmap visualization of the log10 signal of metabolites showed clear clustering of metabolomic profiles by treatment . Features displayed in the heat map were filtered from the total dataset with a p-value < 10−6 and absolute fold change > 5 in roots. Less defined clustering was observed in PLS score plots of distal leaf tissue across sampled timepoints . Ellipses representing the 95% confidence interval for both H2O and AA treatments both partially overlap with the ANE treatment group. Similarly, a heatmap depicting metabolite log10 signal showed more diffuse clustering by treatment . Visualized metabolites from leaves displayed in the heatmap used a p-value < 0.001 and an absolute fold-change > 2. These findings are refilective of distal tissue not directly treated with either elicitor. Changes in the distal leaves were not as robust as in the directly treated roots, likely due to diminution of systemic signals that effect metabolic changes throughout the plant. An assessment of the total annotated features across the metabolomic analysis revealed shared and unique annotated features between roots and leaves .

Roots and leaves share 44 features with leaves displaying the largest number of unique metabolic features . There were 330 unique identified features in leaves compared to 223 features unique to root tissue . A comparison of differential metabolic features for AA- and ANE-treated plants compared to the H2O control revealed robust overlap for both roots and leaves . AA- and ANE-treated roots shared 68 differential metabolic features, with AA and ANE treatments possessing 37 and 29 differential features unique to each, respectively . Less overlap was observed in leaves with 39 shared differential metabolites, with AA- and ANE-root treated plants displaying 34 and 19 uniquely differential metabolites, respectively .Chemical enrichment analyses were conducted to identify classes of metabolites whose accumulation was locally or systemically altered in AA- and ANE-root-treated tomato seedlings. Enrichment analyses of metabolites whose mean signal was significantly changed in AA- or ANE-treated plants compared to H2O identified numerous affected chemical classes . These changes were most robust in directly treated roots compared to distal leaves. Treatment of tomato seedlings with AA showed strong modulation of metabolomic features classified as triterpenoids and linoleic acid and derivatives in roots. AA-treated roots also showed increases in hydroxycinnamic acids and derivatives and fatty acyl glycosides of mono- and disaccharides. ANE-treated roots showed modulation in the accumulation of triterpenoids, steroidal glycosides, and hydroxycinnamic acids and derivatives. Similar to AA-treated plants, the roots of plants treated with ANE also showed increases in metabolites classified as fatty acyl glycosides of mono- and di-saccharides. Although less striking than the chemical enrichment analysis of roots, leaf tissue of root treated plants did reveal an altered metabolome . These changes in metabolite accumulation occurred most prominently at 96 hours, the latest tested time point. Increases in sesquiter penoids and steroidal saponins were seen in leaves of AA-treated plants at 96 hours.

A mix of accumulation and suppression of terpenoids and an increase of methoxyphenols was observed in the leaves of ANE-root-treated plants. Chemical enrichment analyses broadly revealed classes of metabolites that were induced or suppressed in AA- or ANE-treated plants. To examine which specific variables provide the strongest discriminatory power between the two treatment groups, a two-group comparative supervised multivariate analysis, orthogonal projections to latent structures discriminant analysis , was utilized. OPLS-DA score plots show strong between group variability discrimination between AA and ANE treatment groups compared to the H2O control across all tested time points with the x-axis describing the inter-treatment variability,macetas 30l and the y-axis showing the intra-treatment variability . S-plots derived from OPLS-DA were examined for both AA and ANE treatments in pairwise comparison with H2O control. S-plots of OPLS-DA revealed that treatment with AA or ANE induced shared changes in the levels of several defense-related metabolites in roots . Variables with the most negative and positive correlation and covariance values are the most influential in the model. These metabolites are located on either tail of the S-plot and contribute most greatly to the separation between treatment groups Bar charts depicting mean LC-MS signals for top OPLS-DA S-plot metabolites visualized across all time points illustrate that AA and ANE have similar effects on plant metabolic response . Treatment of tomato roots with AA and ANE resulted in a sharp increase in metabolic intermediates in ligno-suberin biosynthesis. This includes AA-induced accumulation of moupinamide and significant increases in coniferyl alcohol in the roots of ANE-treated plants across all tested time points. In roots,AA and ANE treatments also induced increased levels of N-ethyl phydroxycinnamide and N1-trans-feruloylagmatine compared to H2O treatment, refilecting strong upregulation of the shikimate pathway and phenolic compound synthesis. Reduced levels of tomatine and dehydrotomatine were observed in the roots of AA- and ANE-treated plants indicating suppression of steroid glycoalkaloid biosynthesis. Treated plants also showed lower levels of lyso-phosphatidyl ethanolamine that could refilect enhanced membrane lipid turnover. AA and ANE can induce disease resistance locally and systemically, alter the accumulation of key phytohormones, and change the transcriptional profile of tomato with a striking level of overlap between the two treatments . The current study examined and characterized the AA- and ANE-induced metabolomes of tomato. AA and ANE locally and systemically induce metabolome remodeling toward defense-associated metabolic features. Early studies investigating transcriptional and metabolic changes in potato revealed selective partitioning and shifting of terpenoid biosynthesis from steroidal glycoalkaloids to sesquiterpenes following treatment with AA or EPA or challenged with P. infestans . Similarly, our work here with AA- and ANE-treated tomato seedlings has shown a marked decrease in the levels of two abundant glycoalkaloids, tomatine and dehydrotomatine . Our data also show strong enrichment of sesquiterpenes in leaves of AA-treated plants at 96 hours post treatment, although the identity of these sesquiterpenes is unresolved .

This work further supports evidence for differential regulation and sub-functionalization of sterol/ glycoalkaloid and sesquiterpene biosynthetic pathways in solanaceous plants in different stress contexts . AA and EPA are strong elicitors that are abundant in structural and storage lipids of oomycete pathogens, but absent from higher plants. Although their initial perception by the plant is likely different from that of canonical MAMPs , there is some convergence in downstream defenses induced by these various MAMPs. Work to characterize the effect of canonical MAMP treatment on the metabolomes of various plant species has implicated common metabolic changes that prime for defense. Cells and leaf tissue of A. thaliana treated with lipopolysaccharide showed enrichment of phenylpropanoid pathway metabolites, including cinnamic acid derivatives and glycosides . In the same study, SA and JA were also positively correlated with LPS treatment, as we also observed in tomato following treatment with AA . Recent work in A. thaliana wild-type and receptor mutants treated with two chemotypes of LPS showed increases in hydroxycinnamic acid and derivatives and enrichment of the associated phenylpropanoid pathway . Work in tobacco similarly found treatment with LPS, chitosan, and flg22 all induced accumulation of hydroxycinnamic acid and derivatives, and that defense responses elicited by these MAMPs were modulated by both SA and JA . More recent work in the cells of Sorghum bicolor treated with LPS showed enrichment of hydroxycinnamic acids and other phenylpropanoids in coordination with accumulation of both SA and JA . Treatment of tomato with flg22 and flgII-28 also enriched hydroxycinnamic acids, and tomato treatment with cps22 revealed a metabolic shift toward the phenylpropanoid pathway with hydroxycinnamic acid, conjugates and derivatives as key biomarkers . Similar to traditional MAMPs, AA and the AA/EPA-containing complex mixture, ANE, both induce enrichment of cinnamic acid and derivatives in tomato seedlings . This supports the hypothesis that MAMPs broadly induce similar metabolic changes to enrich pools of specialized secondary metabolites that contribute to plant immunity. AA- and ANE-treated roots showed strong enrichment of metabolic features classified as fatty acyl glycosides of mono- and disaccharides . Fatty acyl glycosides have been studied in several plant families and are most extensively characterized in members of Solanaceae . Investigations into the function of fatty acyl glycosides in plants suggest they may act to protect against insect herbivory through various mechanisms and provide protection against fungal pathogens . A recent study isolated and identified fatty acyl glycosides from strawberry capable of inducing immune responses in A. thaliana, including ROS burst, callose deposition, increased expression of defense-related genes, and induced resistance to bacterial and fungal challenge . This same work also demonstrated that the strawberry-derived fatty acyl glycosides induced resistance in soybean and, due to their antimicrobial activity, also protected lemon fruits post harvest from fungal infection . AA- and ANE-root treatments locally elicit accumulation of the same class of defense associated metabolites that Grellet et al. illustrated to have direct antimicrobial activity and protect against disease . Cell wall fortification is an important plant defense often initiated upon pathogen infection. Cell wall lignification is a well-studied mechanism with localized accumulation of phenolic intermediates and lignin at attempted penetration sites . Lignification reinforces and rigidifies the cell wall to create an impervious barrier to microbial ingress . In our study, AA treatment of tomato roots induced accumulation of a phenylcoumaran intermediate in lignin biosynthesis, while ANE treatment induced accumulation of coniferyl alcohol, an important monomer unit of lignin. Interestingly, coniferyl alcohol has recently been shown to act in a signaling capacity in a regulatory feedback mechanism to intricately control lignin biosynthesis, an irreversible process that is energetically costly .

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Technology is likely to be the solution to many of these new problems as well

Furthermore, the percentage increase in gross sales is reduced when growers with sales above the $5 million reporting ceiling accurately report increased acreage but do not report the corresponding increase in gross sales, only the requisite $5 million. Organic fruit crops posted a sales increase of 28 percent between 1998 and 2002, with a 40 percent increase in acreage . The most important commodities for sales growth were strawberries, raspberries, wine grapes, dates, avocadoes, apples, and peaches. Organic wine grapes increased in sales by over $4 million and acreage expanded by over 3,000 acres.In contrast, sales of table grapes almost halved over the period while acreage reduced only slightly.The most important nut crops remained almonds and walnuts, with sizeable increases in sales and acreage for both.Field crops grew in acreage from 1998-2002, with the number of farmed acreage increasing by over 50 percent . One third of the increase in acreage is attributable to pasture and range land paralleling the increase in livestock and dairy production. Another 25 percent reflects increases in rice, alfalfa, and wheat acreage. Rice remained by far the most important field crop during the period but with stagnant sales at around $7 million. Alfalfa was the second most important field crop with sales increasing from less than half a million dollars in 1998 to $1.3 million in 2002. The importance of field crops to organic agriculture remained small, falling from 6 percent of sales in 1998 to less than 5 percent of sales in 2002. This decrease in importance is explained by an absolute decrease in sales over the five year period in almost every region. The decrease in importance is also related to the dramatic increase in sales of livestock, poultry and products. Sales from livestock, poultry,macetas 30l and related products increased by 389 percent over the past five years, although they remained less than 3 percent of the organic industry. Dairy production increased from $4 million to over $11 million.

Sales of organic meat were not permissible prior to 1998 due to differential labeling requirements for organic meat and other foods. Sales of organic chicken reached over $6 million in 2002 with beef and turkey each at about $300,000. Organic eggs sales were $3.6 million in 2002. California agriculture today is known around the world for its diverse product mix, remarkable productivity, and technological sophistication. It is also known for its large-scale farm firms, vertical coordination in food marketing and processing, and, less happily, its environmental problems and farm-labor concerns. The development and adoption of improved technology has been a central element in all of the changes during the twentieth century that have led to the marvel that is today’s California agriculture, and the problems that it faces in the twenty-first century. In this chapter we review the role of new technology in the development of California agriculture, emphasizing the period since World War II.First, we document the changes in the inputs and outputs over the 1949-91 period showing the general trend to save land and labor, to increase the use of capital and purchased inputs, and to increase the output of all categories, but especially vegetables, and nursery and greenhouse marketings. Along with the growth in measured productivity, there have been some important changes in the structure of agriculture as well as in the nature of farms and farming, with a trend to fewer and larger, more specialized farms being an important element of the structural change.The second part of this chapter focuses on the evolution and adoption of various technologies in California agriculture. California is a part of the United States, and its agriculture has shared in many general developments such as the mechanical innovations that displaced the horse over the first half of this century, and other nationwide chemical and biological advances; still, California agriculture remains unlike farming in most of the rest of the country in many ways.

We describe major changes in the elements of technology that have facilitated California’s agricultural development, using examples of mechanical harvesters, pest-control strategies, and irrigation technology. We also discuss some examples of integrated systems involving multiple elements of production technology and marketing—such as the development of tomato varieties that could withstand mechanical harvesting, and the development of new strawberry varieties along with pest-control and production technology to match market requirements. In the last part of the chapter we consider the sources of new agricultural technology and the role of government in providing resources for research and development, as well as institutional structures to facilitate private-sector activity.California agriculture today is very different from what it was in the gold rush years and through the early part of the twentieth century. In the early years, even in this century, there were few people to feed within California, and transportation costs and technology were such that perishable commodities were not economic to produce for shipment over long distances to the population centers in the East. The main focus of the state’s agriculture was on producing grain under dryland conditions, either for human consumption or for livestock feed. Feeding horses was a primary role of California agriculture up through the 1920s. The development of irrigation, transportation infrastructure and technology, postharvest storage and handling technology and facilities, food preservation technology, and the growth of the state’s population, along with the replacement of the horse by motorized vehicles, changed all that. The seeds for the radical transformation of California agriculture during the twentieth century were sown in the last decades of the nineteenth century. In the first chapter of this volume, Olmstead and Rhode provide an overview of the history of California agriculture; they emphasize the role of technology.1 We build on the foundation laid in that chapter. The key elements of technical change have included mechanization , irrigation, agricultural chemicals , improved varieties and other biological improvements, and improved management and information systems. These changes in technology have been made in conjunction with changes in the output and input mix, for related reasons.

Indexes of output in California agriculture in the post-World War II era are shown in Table 1. In terms of total agricultural output, California farmers produced over three times as much in 1991 as in 1949 . Different components of agriculture grew at different rates at different times. For instance, greenhouse and nursery products grew almost tenfold , while output of field crops grew much more slowly . There was considerable variation within individual categories, with some individual products growing very rapidly and others shrinking to negligible amounts. Thus the composition of California production changed markedly over the post-war period. Higher-valued products such as vegetables, greenhouse and nursery products, as well as fruits and nuts, account for a larger share of the value of agricultural output in the 1990s than they did in the immediate post-war period; the shares of livestock and field crops are smaller, accordingly,maceta 25 litros even though all sectors of California agriculture grew significantly over the period. The use of inputs in California agriculture also changed markedly over the postwar period, as seen in Table 2. California agriculture’s use of purchased inputs more than trebled from 1949 to 1991 . The use of capital services—including physical inputs such as automobiles, tractors, trucks and combines, as well as biological inputs such as dairy cows, ewes, and breeder pigs—grew by over 75 percent from 1949 to 1991 . However, quality-adjusted land and labor use in agriculture declined. Land use fell by 8 percent , while labor use decreased by 10 percent . Across all input categories, the index of input use increased by 58 percent, from 100 to 158.That the 237 percent increase in agricultural output was achieved with only a 58 percent increase in agricultural inputs is a reflection of the changing productivity of those inputs. Expressing aggregate output per unit of aggregate input provides a measure of productivity, as shown in Table 3. Productivity in California agriculture doubled between 1949 and 1991 . This means that, if input use had been held constant at the 1949 quantities, using 1991 technology would have resulted in twice as much output as using 1949 technology. Alternatively, to produce the output in 1991 using 1949 technology would require using twice as many inputs as were actually used. In other words, more than half of 1991’s agricultural output is directly attributable to improved technology; and less than half is attributable to conventional inputs. Growth rates of output, input use, and productivity have varied widely from decade to decade. The period of greatest productivity growth was during the 1970s when global commodity markets boomed. The 1980s was a decade of relatively slow growth in output and productivity. Based on similar data ending in 1985, Alston, Pardey, and Carter estimated that the rate of return to public-sector agricultural R&D in California, to which much of that productivity growth could be attributed, was around 20 percent per annum in real terms.3 Complete, specific data on inputs, outputs, and productivity in California and U.S. agriculture, comparable to those in Tables 1 through 3, are not yet available for the years after 1991.However, the data that are available suggest that the 1990s reflected are turn to a more-normal rate of productivity growth in California, sustaining the longer-term average rate, in the range of 2 percent per annum.Mullen et al. applied California’s 1949-1991 average annual agricultural productivity growth rate of 1.81 percent per year to the period 1949-1999. They found that with 1950s productivity and the actual inputs used, output in 1999 would have been only 42 percent of the actual value of $25.3 billion. Hence, the factors that gave rise to productivity growth since 1950 accounted for $14.8 billion worth of output in 1999 alone. Considering the period 1949-1999, Mullen et al. estimated that if public agricultural R&D accounted for one-sixth of the productivity growth the benefit-cost ratio for public investments in agricultural R&D would still be 6:1 . Changes in inputs, outputs, and productivity in California agriculture paralleled similar changes in other states and around the world, but with some important differences reflecting elements unique to California.

As a result of these changes, farms and farming today are very different from what they were in the early part of the twentieth century. Clearly, new technology has been a major driver in the development of California agriculture—and not just agricultural technology. Important changes off the farm have included improvements in methods of food preservation, storage, transport, and handling, along with general improvements in the transportation infrastructure. A host of other technological changes have been applied on the farm. Many of these have been shared with agriculture in other places, and beyond agriculture. In what follows we emphasize those developments that have been specific to California and important here, focusing for the most part on technology applicable at the farm level.The process of technological innovation in California has much in common with the process of technological innovation in the United States more generally. Nonetheless, there are some unique features. Like other regions in the United States in the early part of the twentieth century, changes in technology in California emphasized the adoption of mechanical technology—improved plows, various kinds of harvesting machines that were initially powered by animal power or steam engines, tractors, and so on. All of these innovations reduced costs, especially labor per acre.4 Such mechanical inventions enabled the establishment of land-intensive agriculture and, together with the Homestead Act of 1862, were crucial elements in the settlement of California. As in the rest of the United States, California agricultural production in the twentieth century has grown primarily through increases in yield per acre. California farmers were early in their adoption of chemical inputs such as fertilizers and pesticides, and swiftly took up more advanced agronomic and biological management practices. Recently, California has become the leader in introducing biotechnology and computerized systems into agriculture.Unlike other states, however, the growth of agriculture in California required diversion of water. From the nineteenth century on, California agriculture emphasized the introduction and adoption of institutions and technology to facilitate irrigated agriculture.The institutions ranged from local collective arrangements for diverting the water to massive state water projects. Technology emphasized physical innovations in delivering water to improve control and efficiency. In California, as in other western states, much emphasis was given to improved irrigation technologies.