Author: ecogrow

Elder flowers are frequently used in medicinal and herbal teas, tonics, liqueurs, lemonades, and sparkling waters for their subtle and unique floral, fruity, and green aromas and medicinal properties. Infusions of elder flowers have been used in many cultures for the treatment of inflammation, colds, fever, and respiratory illness and for their diuretic and antidiabetic effects. Some studies have found evidence to support their use, such as antimicrobial activity of elder flower extract against Gram-positive bacteria and high vitro antioxidant activity. Much of the interest for using elder flower in health-promoting applications is based on the high content of biologically active phenolic compounds in the flowers. European and American elder flowers contain an array of phenolic compounds, such as phenolic acids , flavonols , flavonol glycosides [isorhamnetin-3-O-rutinoside , rutin ], flavan-3-ols [-catechin, -epicatechin], and flavanones. In European-grown elder flowers, the dominant phenolic acid and flavonol glycoside include chlorogenic acid and rutin, although isoquercetin, isorhamnetin-3-rutinoside and kaempferol-3-rutinoside are also present. For example, in a study of European elder flowers grown in different locations and altitudes, the dominant class of phenolic compounds were the flavonols, namely rutin , whereas chlorogenic acid levels were lower. This study also found that the flowers contain four times more chlorogenic acid than the leaves or berries. The predominant phenolic compounds identified in elder flower syrup, a traditional herbal beverage, include chlorogenic acid and rutin . There has been only one study on the phenolic profile of the flowers of S. nigra ssp. canadensis which appears to be similar to the European subspecies, container vertical farming in that rutin and chlorogenic acid are the primary flavonol and phenolic acid identified, respectively. The aroma of the elder flower is derived from the volatile organic compounds in the flower and is an important characteristic to understand for consumer acceptance in applications.

To date, only the VOCs of elder flowers from the European subspecies have been studied. The American subspecies S. nigra ssp. canadensis has not yet been investigated. As fresh flowers are highly perishable, many commercial products rely on dry, and in some cases, frozen flowers. Thus, it is important to understand how the organoleptic properties of elder flowers change in response to processing. The VOC profile of tea made with elder flowers of three European cultivars using dynamic headspace sampling revealed compounds important to the characteristic aroma to be linalool, hotrienol, and cis– and trans-rose oxide. Similarly, studies indicate that in fresh and dried flowers analyzed by headspace solid phase microextraction coupled with gas chromatography mass spectrometry , linalool oxides are the main aroma compounds. Linalool oxide has a floral, herbal, earthy, green odor. In hexane extracts of dry elder flowers analyzed via HS-SPME/GC-MS, cis-linalool oxide and 2-hexanone were the primary volatiles. The compound 2-hexanone has a fruity, fungal, meaty, and buttery odor. In syrups made from elder flowers, terpene alcohols and oxides were identified as the primary aroma compounds. Studies of the impact of drying on volatiles in the flowers demonstrate that nearly all types of drying change the volatile profile significantly. The aim of this study was to characterize the composition of phenolic compounds and VOCs in flowers of the blue elderberry , and to determine how these compounds change in response to drying and in the preparation of teas. Understanding how the aroma and phenolic compounds compare with current commercially available European and American subspecies will help to establish a role for blue elder flowers in commercial applications such as herbal teas and as a flavoring for beverages, as well as identify unique compositional qualities of this native and underutilized flower. LC/MS-grade acetonitrile and HPLC-grade hydrochloric acid were purchased from Fisher Scientific .

Purissimum grade phosphoric acid was purchased from Sigma Aldrich and filtered through 0.45 µm polypropylene filters under vacuum. Ascorbic acid was obtained from Acros Organics . Ultrafiltered water was obtained by a Milli-Q system . Analytical standards of rutin, quercetin, chlorogenic acid, and -catechin were purchased from Sigma Aldrich . A standard of n-butyl-d9 was purchased from CDN Isotopes . Kaempferol-3-O-rutinoside, isorhamnetin-3-O-glucoside, IR, and isoquercetin were purchased from ExtraSynthese . Elderflowers were harvested from hedgerows on a farm in Winters, CA in May and June 2021. The latitude and longitude coordinates of the hedgerow are 38.634884, -122.007502. Flowers were harvested between 8 and 10 am and were picked from all sides of the shrub. Picked flowers were placed in plastic bags, immediately put on ice, and transported to the laboratory at the University of California, Davis. Flowers were either dried at 25 °C for 24 h in a dehydrator or analyzed fresh. Once dry, stems were removed, and flowers were stored in oxygen-impermeable aluminum pouches. Triplicate samples of fresh flowers were analyzed for their moisture content by drying 1 g of fresh flowers at 95 °C until a consistent weight was achieved so that the same amount of dry matter could be used for fresh and dry flower analyses. An aqueous mixture of ethanol was used to extract the phenolic compounds from flowers. The optimal mixture of ethanol to water was determined by extracting flowers in 0, 25, 50, 75, and 100% ethanol. Solvents also contained 0.1% HCl and 0.1% ascorbic acid . For each extraction, 0.25 g dry flower material and 25 mL solvent were added to 50 mL Eppendorf tubes. The dry flowers with solvent were homogenized for 1 min at 7000 rpm with a 19 mm diameter probe head in the 50 mL tubes. Homogenized extracts were refrigerated overnight at 4 °C, then centrifuged at 4000 rpm for 7 min . The supernatant was filtered through 0.45 µm PTFE, then diluted 50% with 1.5% phosphoric acid before analysis. Three replicates were made for each extraction condition .

Phenolics were extracted from fresh and dried flowers that were either whole or homogenized. Hence, four types of samples were made: fresh whole flowers , dry whole flowers , fresh homogenized flowers , and dry homogenized flowers . Flowers were mixed with the determined optimal extraction solvent and followed the same extraction process as described above, except whole flower samples were not homogenized and instead placed directly into the refrigerator to extract overnight. All sample extracts were analyzed via high performance liquid chromatography using an Agilent 1200 system with diode array detection and fluorescence detection . Separation of phenolic compounds was performed on an Agilent PLRP-S column at 35 °C, using a previously published method. Mobile phase A was 1.5% phosphoric acid in water and mobile phase B was 80% acetonitrile, 20% mobile phase A . The flow was set at 1.00 mL min-1 . The gradient used was as follows: 0 min, 6% B, 73 min, 31% B, 78-86 min, 62% B, 90-105 min 6% B. Most phenolic compounds were detected using a at 280 nm , 320 nm , and 360 nm . Flavan-3-ols were detected using a fluorescence detector . Compounds were quantified using external standard curves employing surrogate standards for each group of phenolic compounds [-catechin for flavan-3- ols, chlorogenic acid for phenolic acids and simple phenols, quercetin for flavonol aglycones, and IR for flavonols]. Standards were prepared at concentrations of 200, 100, 50, 10, and 5 mg L -1 , except IR which included an additional concentration of 500 mg L -1 . Triplicate analyses of each concentration were performed . Compounds were separated using HPLC-DAD-FLD as described above and identified using authentic standards to check retention time and absorption spectra. Several peaks in the chromatograms did not match tR or spectra of authentic standards. Therefore, hydroponic vertical garden fractions of these peaks were collected. Fractions were dried and reconstituted in 1% formic acid in water. These samples were then subjected to high resolution mass spectrometry using an Agilent 6545 quadrupole time-of-flight mass spectrometer , using conditions previously established for elderberry phenolic compounds.39 Data were then analyzed using Agilent MassHunter Workstation Qualitative Analysis 10.0 . To tentatively identify compounds, the mass to charge ratio of the precursor and fragment ions were compared to online libraries of compounds and using formula generation for the peaks in the spectra.Volatile compounds were analyzed by headspace solid phase microextraction gas chromatography mass spectrometry . The equilibration and extraction parameters were optimized using ground dry flowers, prepared using a spice grinder, pulsed 25 times . A 1 g sample of ground dry flowers was placed into a 20 mL glass vial and the vial was sealed by a crimp-top cap with a Teflon septa. Various incubation temperatures , equilibration times , and extraction times were evaluated to optimize for the highest total peak area and unique compounds identified from samples. The fiber used for all analyses was a divinylbenzene/carbon wide range/polydimethylsiloxane , 23 Ga, 1 cm length, with 80 µm phase thickness . After extraction, the fiber was injected into the GC and volatile compounds were desorbed at 250 °C for 5 min.

Compounds were then separated on a DB-Wax column . Helium was used as a carrier gas at 1 mL min-1 . A temperature program was used with the following steps: 35 °C for 1 min, 3 °C min- 1 to 65 °C, 6 °C min-1 to 180 °C, 30 °C min-1 to 240 °C, hold at 240 °C for 5 min. Total run time was 37.167 min. Compounds were detected with a single quad, triple axis mass spectrometer . The mass range for acquisition was 30 to 300 m/z. The MS transfer line temperature was 250 °C, the source temperature was 230 °C, and the quad temperature was 150 °C. The electron ionization was set to 70 eV. To have the same volume of headspace in fresh and dry flower samples, 0.5 g of fresh whole flowers or 1.5 g ground dry flowers were placed in the 20 mL clear glass vials. For tea samples, 4 mL tea was placed in 20 mL vials. To each sample, 10 µl of 1-butanol-d9 in methanol was added as an internal standard. Volatile compounds were identified using Agilent Mass Hunter Unknown Analysis , using the NIST17 library requiring an ≥ 80% match and that compounds were identified in at least three of the five to be considered a volatile compound in the samples. An alkane series was run under the same chromatographic conditions to determine retention indices. Confirmation of identification was performed by comparing the mass spectra and retention indices with those of standards when possible or literature values when standards were not accessible. Relative response was calculated by normalizing peak area for each compound to the internal standard peak area, and relative peak area was calculated using the relative response of a compound divided by the total peak area of a sample. The phenolic compounds were measured in fresh and dry elder flowers of S. nigra ssp. cerulea, both as whole and as homogenized flowers. The treatments used for this study were chosen to reflect the common ways that elder flowers are used in food and beverage applications and to provide more information on how to best extract the phenolic compounds from the flowers. The moisture content of the elder flowers was determined as 75.6 ± 1.7%. To achieve a consistent dry weight used in extractions, either 1.00 g of fresh flowers or 0.25 g of dry flowers were used. The extraction solvent was optimized to increase extraction efficiency of the main phenolic acids, flavonols and flavan-3-ols which included chlorogenic acid, IR, rutin, and -catechin . While chlorogenic acid, rutin, and catechin could be extracted in either 50:50% ethanol:water or 25:75% ethanol:water for maximum concentrations, the levels of IR increased with increasing amounts of water in the solvent system. However, in solvents containing ≥ 75% water, the flowers turned brown in color suggesting extensive oxidation. Therefore, it was determined that 50:50% ethanol:water was the optimal solvent for the extraction of the range of phenolic compounds in elder flowers without excess oxidation. A recent study of the effect of organicsolvents on the extraction of phytochemicals from butterfly pea flowers also found that 50:50% ethanol:water had optimal extraction properties for the phenolic compounds in flowers. These results differ from a study on the extract of phenolic compounds from dry, powdered European elder flower, which found water to be the optimal extraction solvent, specifically at 100 °C for 30 mins, as compared to 80:20% ethanol:water or 80:20% methanol:water. 

Growers transitioning to more sustainable production systems need information on how management practices affect the physical properties, health, organic matter and water retention of soil. We monitored soil microbial activity for arbuscular mycorrhizal fungi and soil microbial biomass, since weed control and cover-cropping can affect populations of benefi cial soil microbes in annual crops . Many California growers are also willing to plant cover crops because they protect soil from nutrient and sediment loss in winter storms , suppress weeds , harbor beneficial arthropods , enhance vine mineral nutrition and increase soil organic matter . Competition between vines and cover crops for soil moisture in spring, when both are actively growing, can lead to severe water stress and reduce grape production . However, wine-grape production is distinct from other cropping systems because water stress may be imposed to enhance wine composition ; this practice has been studied mostly in high-rainfall regions of California. The vineyard production region of Monterey County, in contrast, has low rainfall , and growers must weigh the benefits of cover crops with the possible need to replace their water use with irrigation. In addition, round plastic pots growers must decide on the type of vegetation to utilize in the middles. Resident vegetation is cheap and generally easy to manage. Cover crops can provide specific benefits such as nitrogen fixation or high biomass production and vigorous roots .

There are many choices for cover crops in vineyard systems, ranging from perennial and annual grasses, to legumes . Each species has strengths and weaknesses, as well as associated seed and management costs. Row weed control treatments were: cultivation, post-emergence weed control only and pre-emergence herbicide , followed by post-emergence herbicide applications . Cultivations and herbicide applications were timed according to grower practices and label rates. Cultivations were carried out every 4 to 6 weeks during the growing season using a Radius Weeder cultivator . The cultivator used a metal knife that ran 2 to 6 inches below the soil surface cutting weeds off in the vine row; it had a sensor that caused it to swing around vines. Pre-emergence herbicides were applied in winter with a standard weed sprayer, and postemergence herbicides were applied in spring through fall as needed with a Patchen Weedseeker light-activated sprayer . An early and late-maturing cereal were chosen for the cover-crop treatments; legumes were not considered due to aggravated gopher and weed problems. Cover-crop treatments in the middles were: no cover crop , earlier maturing ‘Merced’ rye and later maturing ‘Trios 102’ triticale . Cover crops were planted with a vineyard seed drill in a 32-inch-wide strip in the middle of 8-foot-wide rows just before the start of the rainy season in November 2000 to 2004 . They were mowed in spring to protect vines from frost, and both cover-crop species senesced by summer. Prior to planting cover crops each November, row middles were disked to incorporate the previous year’s cover crop and stubble and prepare a seedbed.

Periodic spring and summer disking kept bare-ground middles free of weeds. Weed control and cover-crop treatments were arranged in a 3 x 3 split block design with three replicate blocks covering a total of 23 vineyard rows . Each block contained six vine rows and six adjacent middles. Weed control treatments were applied along the entire length of each vine row ; cover-crop treatments were established along one-third of each middle and were continuous across the main plot treatments in each block. Each replicate main plot-by-subplot treatment combination included 100 vines. Soil compaction. Soil compaction was measured in the vine row in November or December 2003, 2004 and 2005 with a Field Scout Soil SC-900 compaction meter . Ten sites in each plot were sampled to a depth of 15 inches. Soil moisture. Soil water storage was evaluated from volumetric soil moisture measurements taken in-row and adjacent middles to a depth of 3.5 feet at 1-foot intervals using a neutron probe. The neutron probe readings were calibrated with volumetric moisture measured from undisturbed soil cores collected at the site. Rainfall and runoff. A tipping bucket rain gauge with an 8-inch-diameter collector was used to monitor daily and cumulative rainfall at the field site. Runoff was collected at the lower end of the plots into sumps measuring 16 inches in diameter by 5 feet deep. Each sump was equipped with a device constructed from a marine bilge pump, a float switch and flow meter, to automatically record the runoff volume from the plots during storm events. During the second and third years the sampling devices were modified to collect water samples for sediment and nutrient analysis. Vine mineral nutrition. One-hundred whole leaves opposite a fruit cluster were collected from each plot at flowering in May 2003, 2004 and 2005. Petioles were separated from leaf blades, and tissue was immediately dried at 140°F for 48 hours and then sent to the ANR Analytical Laboratory for nutrient analyses. Petiole and leaf-blade tissue samples were analyzed for nitrate , ammonium , nitrogen , phosphorus , potassium , sulfur , calcium , magnesium , boron , zinc , manganese , iron and copper .

Soil mineral nutrition. Composited samples from 10 soil cores taken to a depth of 1 foot were collected from the vine rows and middles at flowering as described above. Samples were air dried and sent to the ANR Analytical Laboratory for analyses. Soil samples were analyzed for pH, organic matter, cation exchange capacity , nitrate, Olsen-phosphorus, potassium, calcium, magnesium, sodium , chloride , boron and zinc. Soil microbial biomass. Due to the limited capacity of the laboratory, microbial biomass assays were conducted on selected treatments. Ten soil cores were collected to a depth of 1 foot and then composite samples were made from each replicate of the pre-emergence and cultivation weed-control treatments and the adjacent middles of the ‘Merced’ rye and bare treatments. Samples were collected about four times each year from November 2001 to November 2005 for a total of 14 sets of samples. Soil samples were immediately placed on ice and taken to the laboratory for soil microbial biomass carbon analysis according Vance et al. . Mycorrhizae. Roots were collected, stained and examined as previously reported on April 16, 2003, May 3, 2004, and June 2, 2005. Grape yield, fruit quality and vine growth. Fruit weight and cluster number were determined by individually harvesting 20 vines per subplot. Prior to harvest a 200-berry sample was collected from each subplot for berry weight and fruit composition. Berries were macerated in a blender and the filtered juice analyzed for soluble solids as Brix using a hand-held, temperature compensating refractometer. Juice pH was measured by pH meter and titratable acidity by titration with a 0.133 normal sodium hydroxide to an 8.20 pH endpoint. At dormancy, shoot number and pruning weights were measured from the same 20 vines. Statistical analysis. Analyses of variance were used to test the effects of cover crop, weed control and year on the vine, soil and microbial parameters, according to a split-block ANOVA model in SAS . Cover crop, weed control, year and their interactions were treated as fixed effects. The main and interactive effects of block were treated as random effects. Year was treated as a repeated measure. When necessary, data were log-transformed to meet the assumption of normality for ANOVA, although untransformed or reverse transformed means are presented. Changes in soil moisture among treatments during the winter and the irrigation seasons were determined from significant treatment-date interactions.We conducted evaluations with a penetrometer each fall to determine the impact of weed-control treatments on soil compaction. Soil compaction was not significantly different at any depth in 2003 . However, in 2004 and 2005 soil compaction began to increase in the cultivation treatment compared to the other two weed-control treatments. In 2004, hydroponic bucket soil compaction at the 4- to 7-inch depth was significantly greater in the cultivation treatment compared to the standard treatment , but not more so than in the post-emergence treatment . In 2005, the cultivation treatment had significantly greater soil compaction at the 4- to 7-inch depth than both the post emergence and standard weed-control treatments . At the 8- to 11-inch depth, soil compaction was significantly greater than the standard treatment , but not greater than in the post-emergence treatment . The blade of the cultivator passes through the soil at 2 to 6 inches deep, which may explain why greater soil compaction was measured there. Cultivations often also occurred when the soil was still moist following an irrigation, which may have contributed to the development of compacted layers over time.Moisture. Average, volumetric soil moisture levels at the 6- to 42-inch depth increased after the first rain events of the season, such as in winter 2002-2003 . Soil moisture declined most rapidly with ‘Merced’ rye in the middles during periods without rainfall each year , presumably due to its greater early-season growth and greater potential evapotranspiration, compared to the ‘Trios 102’ triticale. Soil moisture levels were similar between the bare and ‘Trios 102’ triticale treatments until May for all years. During the irrigation season, average soil moisture levels at the 6- to 42-inch depths were higher in rows than middles. Soil moisture in the rows and middles steadily declined during the irrigation season for all treatments during all years . Moisture levels declined most in middles with ‘Trios 102’ triticale cover during each irrigation season, presumably due to the later growth of this cover crop .

In addition, the row soil-moisture levels also declined the most adjacent to ‘Trios 102’ triticale for the 2003 and 2004 irrigation seasons , but not during the 2005 irrigation season . Runoff. Total precipitation at the field trial was 7.4 inches during the 2002-2003 winter, 7.6 inches during the 2003-2004 winter and 9.9 inches during the 2004-2005 winter. A majority of the runoff was collected during December and January for the 2002-2003 and 2004-2005 winters, and February for the 2003-2004 winter. Cumulative runoff collected from individual plots during the three winters ranged from 0.02% to 3% of seasonal rainfall. Runoff was usually collected during rain events greater than 1 inch per day. Runoff was highest during the second and third years of the trial. During three consecutive winters, runoff was significantly lower in the covercrop treatments . ‘Trios 102’ triticale and ‘Merced’ rye had significantly less runoff than the bare treatment . Suspended sediment and turbidity were also significantly lower in runoff collected from the cover-crop treatments than in bare middles during winter 2004, but nutrient levels were similar among all treatments .Weed control and cover treatments did not have any significant effect on the nutritional status of the grape vines as measured by nutrient levels of the leaf petiole tissues, as determined by ANOVA. Although the nutrient levels by year were significantly different, the interactions of weed control-by-cover and weed control-by cover-by-year were not significant . Weed control and cover treatment also had no significant effect on blade nutrient content with the exception of boron and phosphate content. Vines adjacent to cover crops had significantly lower boron and phosphate levels in the leaf blade tissue than vines adjacent to bare row middles. As with the petioles, there was an absence of significance between the interaction of weed control-by-cover and weed control-by-cover-by-year for all nutrients analyzed .Soil cores indicated that most of the vine roots at this site were located under the vine row and few of the roots extended out to the row middles. This root distribution probably occurred because irrigation water was applied under the vines, and low rainfall at the site does not facilitate root growth into row middles. Thus, the lower nutrient levels in vines near cover crops may have been accentuated by irrigation effects that reduced vine root exploration of the soil to a narrow band under the vines. Since cover-crop roots probably grew into this zone there may have been competition between vines and cover crops for some nutrients. Soil. Cultivated rows had significantly lower levels of nitrate-nitrogen . Although the nutrient levels by year were significantly different, there was an absence of significance between the interaction of weed control-by-cover and weed control-by-cover-by-year . The differences observed in nitrate-nitrogen in the cultivation treatment may be due to the impact of loosening soil on water movement and leaching. Weed control treatments had occasional impacts on soil mineral nutrition in the middles, but results were inconsistent from year to year .

Most metabolic pathways that promote desired quality traits in grape berries are induced during ripening. The onset of ripening is accompanied by significant changes in berry physiology and metabolism, including softening, sugar accumulation, decrease in organic acids, and synthesis of anthocyanins and other secondary metabolites that define the sensory properties of the fruit . Berry ripening is controlled by multiple regulatory pathways, and occurs in an organized and developmentally timed manner. Interactions between transcriptional regulators and plant hormones regulate the initiation and progression of ripening processes . Like other non-climacteric fruit, grape berries do not display a strong induction of ethylene production and respiration rate at véraison, and the activation of ripening events does not depend primarily on ethylene signaling. Even though the hormonal control of grape berry development is not completely understood, it is established that abscisic acid , brassinosteroids, and ethylene are positive regulators of ripening processes, while auxin delays the initiation of ripening . In the context of virus–grape berry interactions, dissecting the mechanisms that regulate ripening and plant defenses may provide new opportunities to develop vineyard management strategies to control viral diseases and ameliorate the negative effects on berry quality. In this study, we integrated genome-wide transcriptional profiling, stackable planters targeted chemical and biochemical analyses, and demonstrated that grapevine red blotch disrupts ripening and metabolism of red-skinned berries.

We sampled berries at different ripening stages from vines infected with GRBaV and healthy vines in two vineyards. We identified grape metabolic pathways that were altered in ripening berries because of the viral infection. We determined that GRBaV-induced pathways that are normally associated with early fruit development in berries at late stages of ripening, and suppressed secondary metabolic pathways that occur during normal berry ripening and/ or in response to stress. Using targeted metabolite profiling and enzyme activity analyses, we confirmed the impact of GRBaV on phenylpropanoid metabolism. Remarkably, these processes included alterations in ripening regulatory networks mediated by transcriptional factors, post-transcriptional control, and plant hormones, which lead to berry developmental defects caused by red blotch.To determine the impact of grapevine red blotch on berry physiology, we studied naturally occurring GRBaV infections in distinct wine grape-growing regions in northern California . We sampled red-skinned grape berries from two different vineyards, one in Oakville and one in Healdsburg . We used multiple vineyard sites to focus on observations consistently made across environments and, thus, to exclude factors associated with specific environmental or cultural conditions. Prior to sampling, vines were screened for the presence of GRBaV and other common grapevine viruses. The appearance of red blotch symptoms on leaves of GRBaV-positive vines and not on those of healthy controls confirmed the initial viral testing. We sampled grape berries from vines that tested positive for GRBaV and negative for other common grapevine viruses. At the same time, we also collected berries from vines that tested negative for all viruses and included them in the study as healthy controls. In order to determine the impact of the disease on berry development and metabolism, we collected GRBaV-positive and control berries at comparable developmental stages: pre-véraison , véraison , post-véraison , and harvest . This sampling strategy also aimed to limit confounding effects due to differences in the progression of ripening between berry clusters of GRBaV-positive and healthy vines. In some cases, we observed that GRBaV-positive vines presented grape clusters with evident uneven ripening .

Comparisons between berries from GRBaV-positive vines and healthy controls indicated that, at equivalent stages of development, berries affected by red blotch had reduced soluble solids and total anthocyanins in agreement with previous reports on red-skinned wine grapes . Sampled berries were used for genome-wide transcriptional profiling of viral and grape genes. RNAseq was performed using 3–4 biological replicates of each ripening stage, infection status, and vineyard. We first confirmed the presence of the virus in the berries of GRBaV-positive vines by qPCR amplification of viral DNA . Viral activity in the berries was also assessed by quantifying plant-derived mRNA transcripts of GRBaV genes in the RNAseq data. Plant expression of five out of the six predicted genes in the GRBaV genome was detected in all berry samples obtained from GRBaV-positive vines but not in berries collected from the control vines . The most expressed GRBaV genes in the berries corresponded to V1, which encodes a coat protein, and V3 with unknown function. Expression levels of the GRBaV genes appeared to change as berries ripened. However, we could not determine to what extent the progression of ripening or other environmental factors influenced the plant’s transcription of viral genes because their pattern of variation between ripening stages differed in the two vineyards . Expression of 25 994 grape genes was detected by RNAseq across all berry samples. Principal component analysis was carried out with the normalized read counts of all detected genes. The two major PCs, which together accounted for 42.97% of the total variability, clearly separated the samples based on ripening stage, regardless of the vineyard of origin or their infection status . These results indicated that the intervineyard variation was smaller than the ripening effect, and the overall progression of ripening was similar between berries from GRBaV-positive and control vines.

Therefore, we hypothesized that GRBaV infections in berries have altered the expression of particular grape genes and/or molecular pathways, which could subsequently have led to developmental and metabolic defects.While the PCA described above indicated that overall transcriptome dynamics associated with berry ripening were not perturbed by the infection, the lower levels of soluble solids and anthocyanins in GRBaV-positive berries, particularly later in development, suggested that red blotch may affect specific primary and secondary metabolic processes. We therefore focused the RNAseq analyses to identify grape molecular pathways that were differentially regulated as a result of GRBaV infections. We identified grape genes with significant differential expression due to red blotch by comparing GRBaV-positive and GRBaV-negative berries at each ripening stage and independently for each vineyard. We then looked at the intersection of differentially expressed genes between the two vineyards to identify common responses to red blotch. A total of 932 grape DE genes were found to be consistently down- or up-regulated in infected berries in both vineyards at a given ripening stage, and were classified as GRBaV-responsive genes . On average these GRBaV-responsive genes showed 0.49 ± 0.22-fold changes compared with the healthy controls. Comparing berries at similar ripening stages may have contributed to exclude more dramatic changes in gene expression associated with more pronounced ripening delay due to GRBaV. Key metabolic processes that were suppressed or induced as a consequence of red blotch in ripening berries were identified by enrichment analyses of the functional categories defined by Grimplet et al. in the set of GRBaV-responsive genes . GRBaV infections altered the transcription of several primary metabolic pathways. Amino acid biosynthetic pathways were repressed in GRBaV-positive berries, while amino acid catabolic pathways were induced. Changes in carbohydrate metabolism were also observed; in particular, genes involved in glycolysis/gluconeogenesis and starch metabolism had reduced expression in GRBaV-infected berries. Genes involved in nucleic acid metabolism, including RNA processing and surveillance, showed higher expression in GRBaV-infected berries. These pathways coincided at véraison with the induction of genes involved in stress responses to virus . RNA metabolic pathways are commonly altered in plants during viral infections and have been related to resistance or susceptibility depending on the particular plant–virus interaction . Red blotch also impacted the transcription of several abiotic stress response pathways. In particular, berries after véraison showed lower expression of genes encoding hypoxia responsive proteins and heat stress transcription factors, among others . A prominent feature of the GRBaV-positive berries was the transcriptional suppression of secondary metabolic pathways, stacking pots in particular the biosynthesis of phenylpropanoids, stilbenoids, and lignin . Because the lower anthocyanin content observed in the GRBaV-positive berries may have resulted from reduced metabolic flux in the core phenylpropanoid pathway and alterations in flavonoid and anthocyanin biosynthesis, we pursued a deeper evaluation of these pathways using an integrated approach of transcriptional and metabolite profiling coupled to enzymatic analyses.Most enzymes involved in phenylpropanoid metabolism are encoded by large gene families. There is also high redundancy among these genes, which ensures the functional integrity and plasticity of the phenylpropanoid-related pathways . Therefore, to test the hypothesis that the red blotch-induced transcriptional changes had an actual impact on phenylpropanoid metabolism, we measured the activity of key enzymes and the abundance of compounds involved in these pathways . We detected significant reductions in activity of seven enzymes that catalyze important steps in the core phenylpropanoid, stilbene, flavonoid, and anthocyanin biosynthetic pathways due to GRBaV infections of berries at three ripening stages . In addition, the first enzyme committed to flavone and flavonol biosynthesis, flavonol synthase , had significantly lower activity at post-véraison and harvest stages .

Red blotch altered the accumulation of 17 compounds that result from the phenylpropanoid metabolism and two compounds upstream of this pathway, shikimic acid and gallic acid . Most of these compounds showed significantly lower abundance in the GRBaV-positive berries compared with the controls at later stages of ripening. The main anthocyanins present in grape berries: malvidin-3-O-glucoside, petunidin-3-O-glucoside, delphinidin-3-O-glucoside, pelargodin-3-O-glucoside, and cyanidin-3-O-glucoside, were significantly reduced by red blotch at harvest. Gallic acid, sinapic acid, and quercetin also showed lower abundance in infected berries. Few exceptions to this general suppression of phenolic accumulation were the accumulation of the precursor shikimic acid, which significantly increased in infected berries at harvest, and of resveratrol that showed significantly greater accumulation at véraison and postvéraison. Additional experiments are necessary to understand the accumulation of these two metabolites in the presence of GRBaV: preliminarily, we can hypothesize that the higher abundance of resveratrol is due either to a restriction of subsequent enzymatic steps in stilbene metabolism for which this compound is a substrate, or to the enzymatic hydrolysis of resveratrol glycosides or stilbenoid dimers previously synthesized. The integrated analysis of transcriptomic, metabolite, and enzyme activity data supported a general repression of the core and peripheral phenylpropanoid pathways, which are normally triggered in red-skinned berries throughout ripening and in response to stress . These results suggest that GRBaV infections disrupt secondary metabolic pathways by altering the regulation of berry ripening processes and/or signaling mechanisms related to plant defense. Interestingly, GRBaV infections seemed to have a more a pronounced impact on enzymatic activities and metabolite accumulation than on the expression levels of the genes in the pathway, which in general displayed small fold change differences between healthy and infected samples. This observation further confirms the importance of evaluating metabolic perturbations at multiple regulatory levels.Understanding how plants respond to external stimuli in the field is crucial to improve agricultural traits under naturally fluctuating conditions. Most studies on plant–pathogen interactions are performed with model organisms in the greenhouse or laboratory, which reduce the confounding effects of the environment, but also challenge the reproducibility of the results in the field . Compatible plant–virus interactions in perennial woody crops are complex due to the presence of multiple and systemic infections,tissue and developmental stage-specific responses, differences between species and cultivars, and the combination of biotic and abiotic factors during the crop season . The application of a system biology approach to study red blotch under multiple vineyard conditions allowed us to explore grapevine responses to GRBaV infections in real agronomic settings and to characterize the influence of viral activity on berry physiology. In almost all viral diseases occurring in the vineyard, the virus is distributed systemically throughout the grapevine. Once introduced in the host, viral particles move rapidly within the vascular tissue towards sink tissues and establish infections . Although we detected the presence of GRBaV in vegetative and berry tissues during growing and harvest seasons, symptoms of red blotch were only evident after véraison, which suggests that the disease onset is mostly dependent on grapevine phenology and not necessarily linked to viral accumulation. Similar observations have been made during grapevine leafroll disease, supporting the hypothesis that the appearance of viral disease symptoms in the vineyard may result from the interaction between pathogen and host cellular factors at specific phenological stages . Whether GRBaV is able to modulate its infection strategy as a function of plant development and/ or grapevines have distinct responses to red blotch throughout the season remains to be resolved. GRBaV shares several similarities with geminiviruses, including a small singlestranded DNA genome that encodes six potential proteins .

In vineyards, studies in California in the late 1990s have reported net primary productivity or total biomass values between 550 g C m−2 and 1100 g C m−2. In terms of spatial distribution, some data of standing biomass collected by Kroodsma et al. from companies that remove trees and vines in California yielded values of 1.0–1.3 Mg C ha−1  year−1 woody C for nuts and stone fruit species, and 0.2–0.4 Mg C ha−1  year−1 for vineyards. It has been reported that mature California orchard crops allocate, on average, one third of their NPP to the harvested portion and mature vines 35–50% of the current year’s production to grape clusters. Pruning weight has also been quantified by two direct measurements which estimated 2.5 Mg of pruned biomass per ha for both almonds and vineyards. The incorporation of trees or shrubs in agroforestry systems can increase the amount of carbon sequestered compared to a monoculture field of crop plants or pasture. Additional forest planting would be needed to offset current net annual loss of above ground C, representing an opportunity for viticulture to incorporate the surrounding woodlands into the system. A study assessing C storage in California vineyards found that on average, surrounding forested wild lands had 12 times more above ground woody C than vineyards and even the largest vines had only about one-fourth of the woody biomass per ha of the adjacent wooded wildlands .The objectives of this study were to: measure standing vine biomass and calculate C stocks in Cabernet Sauvignon vines by field sampling the major biomass fractions ; calculate C fractions in berry clusters to assess C mass that could be returned to the vineyard from the winery in the form of rachis and pomace; determine proportion of perennially sequestered and annually produced C stocks using easy to measure physical vine properties ; and develop allometric relationships to provide growers and land managers with a method to rapidly assess vineyard C stocks.

Lastly, we validate block level estimates of C with volumetric measurements of vine biomass generated during vineyard removal.The study site is located in southern Sacramento County, California, USA , nft channel and the vineyard is part of a property annexed into a seasonal floodplain restoration program, which has since removed the levee preventing seasonal flooding. The ensuing vineyard removal allowed destructive sampling for biomass measurements and subsequent C quantification. The vineyard is considered part of the Cosumnes River appellation within the Lodi American Viticultural Area, a region characterized by its Mediterranean climate— cool wet winters and warm dry summers—and by nearby Sacramento-San Joaquin Delta breezes that moderate peak summer temperatures compared to areas north and south of this location. The study site is characterized by a mean summer maximum air temperature of 32 °C, has an annual average precipitation of 90 mm, typically all received as rain from November to April. During summer time, the daily high air temperatures average 24 °C, and daily lows average 10 °C. Winter temperatures range from an average low 5 °C to average high 15 °C. Total heating degree days for the site are approximately 3420 and the frost-free season is approximately 360 days annually. Similar to other vineyards in the Lodi region, the site is situated on an extensive alluvial terrace landform formed by Sierra Nevada outwash with a San Joaquin Series soil . This soil-landform relationship is extensive, covering approximately 160,000 ha across the eastern Central Valley and it is used extensively for winegrape production. The dominant soil texture is clay loam with some sandy clay loam sectors; mean soil C content, based on three characteristic grab samples processed by the UC Davis Analytical Lab, in the upper 8 cm was 1.35% and in the lower 8–15 cm was 1.1% .

The vineyard plot consisted of 7.5 ha of Cabernet Sauvignon vines, planted in 1996 at a density of 1631 plants ha−1 with flood irrigation during spring and summer seasons. The vines were trained using a quadrilateral trellis system with two parallelcordons and a modified Double Geneva Curtain structure attached to T-posts . Atypically, these vines were not grafted to rootstock, which is used often in the region to modify vigor or limit disease .In Sept.–Oct. of 2011, above ground biomass was measured from 72 vines. The vineyard was divided equally in twelve randomly assigned blocks, and six individual vines from each block were processed into major biomass categories of leaf, fruit, cane and trunk plus cordon . Grape berry clusters were collected in buckets, with fruit separated and weighed fresh in the field. Leaves and canes were collected separately in burlap sacks, and the trunks and cordons were tagged. Biomass was transported off site to partially air dry on wire racks and then fully dried in large ventilated ovens. Plant tissues were dried at 60 °C for 48 h and then ground to pass through a 250 μm mesh sieve using a Thomas Wiley® Mini-Mill . Total C in plant tissues was analyzed using a PDZ Europa ANCA-GSL elemental analyzer at the UC Davis Stable Isotope Facility. For cluster and berry C estimations, grape clusters were randomly selected from all repetitions. Berries were removed from cluster rachis. While the berries were frozen, the seeds and skins were separated from the fruit flesh or “pulp”, and combined with the juice . The rachis, skins and seeds were dried in oven and weighed. The pulp was separated from the juice + pulp with vacuum filtration using a pre-weighed Q2 filter paper .

The largest portion of grape juice soluble solids are sugars. Sugars were measured at 25% using a Refractometer PAL-1 . The C content of sugar was calculated at 42% using the formula of sucrose. Below ground biomass was measured by pneumatically excavating the root system with compressed air applied at 0.7 Mpa for three of the 12 sampling blocks, exposing two vines each in 8 m3 pits. The soil was prewetted prior to excavation to facilitate removal and minimize root damage. A root restricting duripan, common in this soil, provided an effective rooting depth of about 40 cm at this site with only 5–10 fine and small roots able to penetrate below this depth in each plot. Roots were washed, cut into smaller segments and separated into four size classes , oven-dried at 60 °C for 48 h and weighed. Larger roots were left in the oven for 4 days. Stumps were considered part of the root system for this analysis.In vineyard ecosystems, hydroponic nft annual C is represented by fruit, leaves and canes, and is either removed from the system and/or incorporated into the soil C pools, which was not considered further. Structures whose tissues remain in the plant were considered perennial C. Woody biomass volumes were measured and used for perennial C estimates. Cordon and trunk diameters were measured using a digital caliper at four locations per piece and averaged, and lengths were measured with a calibrated tape. Sixty vines were used for the analysis; twelve vines were omitted due to missing values in one or more vine fractions. All statistical estimates were conducted in R .An earth moving machine was used to uproot vines and gather them together to form mounds. Twenty-six mounds consisting of trunks plus cordons and canes were measured across this vineyard block . The mounds represented comparable spatial footprints within the vineyard area . Mound C stocks were estimated using their biomass contribution areas, physical size, density and either a semi-ovoid or hemispherical model.A real-time kinematic global positioning system was used to map boundaries of each mound, with vertices placed every 1.5 m to measure circumference. Average mound height was calculated using a stadia rod and laser inclinometer range finder. The circumsurficial distance over the major axes of each mound was measured with a calibrated cord. Combined, these measurements were used to estimate pile volume using semi-ovoid and hemispherical models .The present study provides results for an assessment of vineyard biomass that is comparable with data from previous studies, as well as estimates of below ground biomass that are more precise than previous reports. While most studies on C sequestration in vineyards have focused on soil C, some have quantified above ground biomass and C stocks. For example, a study of grapevines in California found net primary productivity values between 5.5 and 11 Mg C ha−1 —figures that are comparable to our mean estimate of 12.4 Mg C ha−1 . For pruned biomass, our estimate of 1.1 Mg C ha−1 were comparable to two assessments that estimated 2.5 Mg of pruned biomass ha−1 for both almonds and vineyards.

Researchers reported that mature orchard crops in California allocated, on average, one third of their NPP to harvestable biomass, and mature vines allocated 35–50% of that year’s production to grape clusters. Our estimate of 50% of annual biomass C allocated to harvested clusters represent the fraction of the structures grown during the season . Furthermore, if woody annual increments were considered this proportion would be even lower. Likewise the observed 1.7 Mg ha−1 in fruit represents ~14% of total biomass , which is within 10% of other studies in the region at similar vine densities. More importantly, this study reports the fraction of C that could be recovered from winemaking and returned to the soil for potential long term storage. However, this study is restricted to the agronomic and environmental conditions of the site, and the methodology would require validation and potential adjustment in other locations and conditions. Few studies have conducted a thorough evaluation of below ground vine biomass in vineyards, although Elderfield did estimate that fine roots contributed 20–30% of total NPP and that C was responsible for 45% of that dry matter. More recently, Brunori et al. studied the capability of grapevines to efficiently store C throughout the growing season and found that root systems contributed to between 9 and 26% of the total vine C fixation in a model Vitis vinifera sativa L. cv Merlot/berlandieri rupestris vineyard. The results of our study provide a utilitarian analysis of C storage in mature wine grape vines, including above and below ground fractions and annual vs. perennial allocations. Such information constitutes the basic unit of measurement from which one can then estimate the contribution of wine grapes to C budgets at multiple scales— fruit, plant or vineyard level—and by region, sector, or in mixed crop analyses. Our study builds on earlier research that focused on the basic physiology, development and allocation of biomass in vines. Previous research has also examined vineyard-level carbon at the landscape level with coarser estimates of the absolute C storage capacity of vines of different ages, as well as the relative contribution of vines and woody biomass in natural vegetation in mixed vineyard-wildland landscapes. The combination of findings from those studies, together with the more precise and complete carbon-by-vine structure assessment provided here, mean that managers now have access to methods and analytical tools that allow precise and detailed C estimates from the individual vine to whole-farm scales. As carbon accounting in vineyard landscapes becomes more sophisticated, widespread and economically relevant, such vineyard-level analyses will become increasingly important for informing management decisions. The greater vine-level measuring precision that this study affords should also translate into improved scaled-up C assessments . In California alone, for example, there are more than 230,000 ha are planted in vines. Given that for many, if not most of those hectares, the exact number of individual vines is known, it is easy to see how improvements in vine-level measuring accuracy can have benefits from the individual farmer to the entire sector. Previous efforts to develop rough allometric woody biomass equations for vines notwithstanding, there is still a need to improve our precision in estimating of how biomass changes with different parameters. Because the present analysis was conducted for 15 year old Cabernet vines, there is now a need for calibrating how vine C varies with age, varietal and training system. There is also uncertainty around the influence of grafting onto rootstock on C accumulation in vines. As mentioned in the methods, the vines in this study were not grafted—an artifact of the root-limiting duripan approximately 50 cm below the soil surface.

The farms in the sample that monocrop do so on the vast majority of their farm, not just on specific plots. In each survey year over half of the plots being monocropped are growing maize, with approximately 10% each growing beans and coffee. As shown in Table B.3.1 of Appendix B.3, there is no discernible difference in monocropping across farm sizes, although ejido farms are marginally more likely to employ monocropping than non-ejido farms. To account for potentially persistent negative productivity shocks we generate a dummy variables for whether the household suffered crop or livestock loss in either of the previous two years. The MxFLS asks households about their participation in a variety of government programs. The two most important programs are Progresa/Oportunidades and Procampo. Procampo is an income transfer program designed to support agricultural producers of staple crops. Progresa, later renamed Oportunidades, is a conditional cash transfer program designed to combat poverty and incentivize investments in children. Data limitations do not allow us complete information on participation in Progresa14 so we focus exclusively on participation in Procampo. Table B.3.1 in Appendix B.3 shows the share of farms participating in Procampo by year and farm size. With the exception of the largest farms, participation increases with farm size. In addition, nft system we consider participation in Alianza, a government-run program designed to aid farmers’ transition into crops for export.

While less than 3% of the sample participated in this program in any survey round, we consider participation in this program for its potentially important impact on farmers. Having access to credit is an important determinant of agricultural productivity, and the existence of credit constraints and differential access to credit is one theoretical source of a relationship between farm size and productivity. Table B.3.3 in Appendix B.3 shows “access to credit” by farm size, where a household is considered to have access if the household head knows where they can go to borrow or ask for a loan. This is a crude measure as it does not account for credit rationing and the likelihood that a household could succeed in obtaining a loan. A follow up question regarding the source of that credit allows us to identify if access is through a formal or an informal financial institution. There are no clear relationships between farm size and this measure of access to credit. We introduce an indicator variable to control for access to formal lines of credit.As with much of the literature, we begin the discussion of the farm size – productivity relationship using land productivity, measured as output per hectare. Figure 2.1 shows the non-parametric relationship between the log of farm size and the log of output per hectare in 2002, where output is measured using the Fisher quantity index. There is a clear inverse relationship between farm size and land productivity over the entire range of farm sizes, and while not shown here this relationship is strikingly consistent across the three survey waves. Land productivity falls rapidly up to approximately 1 ha, at which point the relationship levels before resuming a dramatic decline in land productivity after approximately 20 ha.As shown in chapter 1, an inverse relationship between farm size and land productivity is neither necessary nor sufficient for the existence of an inverse relationship between farm size and total factor productivity. For reference, the linear relationship between land productivity and farm size is estimated.

Farm size is inversely related to land productivity at the 1% level of significance, as shown in column 1 of Table 2.6, where we estimate the elasticity of land productivity with respect to farm size to be -0.82. We then estimate the average production function identified by equation assuming four alternate specifications of the farm size – productivity relationship that vary in their flexibility. These regressions measure output using the quantity index, weight observations by the expansion factors provided by MxFLS, use the preferred measure of the family labor index, employ community fixed effects, and cluster standard errors at the community level. Coefficients for the farm size variables, the primary variables of interest, are displayed in Table 2.6. Table 2.7 displays the coefficients for additional household controls, and technology coefficients are included as Table B.4.1 of Appendix B.4. The results indicate an inverse relationship between farm size and TFP, as shown by the negative and statistically significant coefficient on the linear Farm Size variable in model 2. In the sample, a 1% increase in farms size is associated with a 0.81% decrease in output per hectare, ceteris paribus. The farm size coefficient is slightly less negative than in model 1, but not statistically different, indicating that the relationships between farm size and land productivity and farm size and TFP are almost identical in this sample. Models 3 and 4 allow for a quadratic and cubic relationship between farm size and TFP, but the coefficients on the higher ordered terms are either not statistically significant or do not have a noticeable impact on the linear model. Model 5 captures some nonlinearity in the farm size – TFP relationship by using dummy variables for 7 farm size bins.The smallest of farms, those less than one half of a hectare, are significantly more productive than all other farms, while the largest, those greater than 20 hectares, are significantly less productive than all smaller farms.

Productivity between these two extremes, however, appears relatively stable. This closely mirrors the non-parametric relationships between farm size and land productivity shown in Figure 2.1, highlighting the need to assume a flexible functional form to fully understand the farm size – productivity relationship. The linear relationships identified in the parametric specifications 2 through 4 do not capture these subtleties. We see little change in the inverse relationship over time across all models, as none of the farm size and survey year interaction terms are statistically significant. The finding of a time invariant inverse relationship between farm size and productivity – when using both land productivity and TFP – suggests that the IR is alive and well in Mexico. There is, however, evidence for a decline in average productivity over time in this sample, as the 2009 dummy variable is negative and statistically significant. Results for the household explanatory variables, displayed in Table 2.7, show that monocropping and operating as a subsistence farm have a consistently negatively relationship with TFP. In contrast, participating in Procampo is positively associated with productivity . It is important to reiterate that these are potentially endogenous explanatory variables, hydroponic gutter and we should not interpret the coefficients as identifying causal relationships. Having more education is positively related to TFP, but with the exception of a college education these results are not consistently statistically significant at standard levels. Estimates of equation explore heterogeneity in the farm size – productivity relationship across different groups of Mexican family farms by interacting indicator variables for those groups with farm size. For simplicity, we assume the farm size – TFP relationship to be linear and time invariant. 17 Table 2.8 displays the results from interacting farm size with being located in the more commercially oriented agricultural region of Northern Mexico, participation in Procampo, practicing monocropping, operating as a subsistence farm, and whether or not the household head has any education beyond secondary school. Overall, the farm size – TFP relationship remains stable, as none of these additional interactions contribute to explaining the farm size – TFP relationship that we have identified. 18 In addition, we interact controls for farms having ejido status, various forms of property rights, and access to credit in Table 2.9. These are of special interest given the reforms of the ejido system and rural credit markets. Again, the IR is unaltered across these subgroups as these interactions are not statistically significant. The relationship between farm size and TFP is the same for ejido farms as for non-ejido farms, is the same regardless of how property rights are documented, and is the same whether or not farms have access to formal credit markets.The farm-size – TFP relationship is subjected to a series of robustness tests. We assume the farm size – TFP relationship is best captured by the linear and dummy variable models used above, as the quadratic and cubic models provide little additional information. Table 2.10 contains the results from the linear models and Table 2.11 from the dummy variable specification. First, model 1 introduces household-level fixed effects to control for timeinvariant, unobserved, household heterogeneity. The model omits time-invariant household controls, clusters standard errors at the household level, and provides a superior approach to addressing potential omitted variable biasrelative to the model with community level fixed effects. Second, model 2 tests the sensitivity of the relationship to decisions regarding the construction of the family labor index by using an alternative index of family labor described in Appendix B.2. Third, we test the impact of choice of weighting of the observations.

Whereas the core results apply the MxFLS weights designed to make the sample statistically representative of Mexican households in each survey year, model 3 shows results when we apply no weighting at all. We explore sensitivity to the use of weights because we are interested in Mexican agriculture, not rural Mexican households, and the treatment of the data reduces the sample size; therefore, it is not clear that these weights remain appropriate. Fourth, model 4 uses an alternative measure of the dependent variable – farm output. Whereas the core results uses the preferred approach of calculating a quantity index for each household , model 4 deflates the nominal value of production in each year for each household and uses the real value of output . Lastly, model 5 uses the real value of output as in model 4, but estimates the relationship over the repeated cross-sections. This final robustness check speaks to the potential for households to be selecting into or out of the unbalanced panel. Overall, these alternative treatments of the data generate qualitatively similar results to the core regressions in Table 2.6 for our primary variables of interest. This is true in terms of the coefficient signs and orders of magnitude. The exception is model 2 using the alternative index of family labor, for which the farm size coefficients are diminished in magnitude although negative and still statistically significant. The consistency across models is reassuring that treatment of the data is not driving the core results regarding the farm size – TFP relationship. In similar fashion, estimated coefficients on household explanatory variables are quite robust. The coefficients identifying farms engaged in monocropping and operating as subsistence farms remain negative and statistically significant in almost all of the robustness exercises, while the coefficients for participation in Procampo and college education remain positive and statistically significant. In results not shown here, we estimate the core models using crop production only in measuring output and the conclusions regarding the farm size – productivity relationship are robust to this dimension as well.Estimating a stochastic frontier complements analysis of the average production function by identifying productivity at the frontier and production inefficiencies. Together, these components determine average TFP identified with the average production function. In similar fashion, whereas the estimation of the average production function allows us to assess the relationship between farm size and average productivity, stochastic frontier analysis allows us to assess any relationships between farm size and productivity at the technical frontier and between farm size and technical inefficiency. The results of five specifications of the stochastic production frontier are shown in Table 2.12, with the top and bottom panels displaying the results from the frontier and variance of inefficiency equations, respectively. Model 1, the baseline model, has no additional household controls in either the frontier or the inefficiency equations . Model 2 includes dummy variables for the household head’s level of education in the frontier equation and includes a dummy variable for the household head being of indigenous ethnicity in the inefficiency equation. Model 3 alternatively assumes that education of the household head should be included as a control in the inefficiency equation but not the frontier equation. Model 4 assumes that education belongs in both equations. Model 5 includes education in the frontier equation only, adding interaction terms between farm size and the survey year dummies in both the frontier and the inefficiency equations.

In 1998, there were no yield differences among the vegetable rotation plots; however, in 2000,broccoli rotation plots had the highest and lettuce plots had the lowest strawberry yield, with the yield in cauliflower rotation plots being intermediate. Strawberry production under fumigation incurred the highest production costs but also provided the highest returns. Average total cost of production in 1998 and 2000 was estimated to be $81,000 per hectare with a net profit of $10,500 per hectare . In contrast, the cost of strawberry production without fumigation decreased to an estimated $77,000 to 79,000 but also led to losses between $17,000 and 19,000 depending on the production site . Production of strawberry under crop rotation involved giving up the annual strawberry production during the time rotation crops were grown but resulted in net profits because of income from rotation crops and higher strawberry yield. However, the overall profits were reduced by 20 to 30% a year relative to the production under fumigation. The total cost of producing strawberry following two crops of broccoli was estimated to be nearly $82,000 that resulted in a net profit of $6,800 to 7,800 per hectare per year, depending on location . This study demonstrated that rotations with broccoli and Brussels sprouts followed by the post harvest incorporation of the respective residues reduced the number of V. dahliae microsclerotia in soil that resulted in concomitant reductions in the incidence of Verticillium wilt and increases in fruit yield of strawberry.

None of the rotations, however, hydroponic dutch buckets reduced Verticillium wilt or increased yield as much as fumigation with methyl bromide + chloropicrin. The benefits of rotations were more evident with broccoli than with Brussels sprouts. Although the results with broccoli rotations are consistent with those obtained on cauliflower , this is the first demonstration of successful rotations with broccoli and Brussels sprouts on a highly Verticillium wilt-sensitive, deep-rooted , and long-duration crop such as strawberry. Rotations with lettuce increased the numbers of microsclerotia in soil significantly over pre-rotation levels consistent with it being identified as a new host of V. dahliae and the strawberry strain being pathogenic on lettuce and vice versa . None of the rotations influenced the overall populations of Pythium spp. in soil, but it was unclear whether specific rotations influenced the species composition of this population. This often was not apparent on strawberry plants because disease caused by Pythium spp. does not have distinct symptoms on this host that enable diagnosis based on visual symptoms alone . Adaptation of successful rotations with broccoli entails giving up the annual strawberry production following fumigation during rotation and nearly 30% of the annual profits on a per hectare basis. While these short-term losses accrue, growers reap the benefits of reducing soil inoculum over the long-term. As with cauliflower , the greatest reduction in the number of microsclerotia at the Watsonville site was observed soon after the incorporation of broccoli and Brussels sprouts residues. This was followed by additional reductions in microsclerotia of V. dahliae during the second cycle of broccoli rotation. The numbers of microsclerotia increased marginally in broccoli plots during the subsequent strawberry season but remained lower than in the Brussels sprouts plots.

In contrast, at the Salinas site, even with no detectable V. dahliae propagules, broccoli rotations increased strawberry yields as evidenced by higher plant health ratings, suggesting that broccoli may suppress pathogens other than V. dahliae or result in enhanced growth of strawberry plants. Even though this study focused on Verticillium and Pythium spp., other soilborne pathogens such as R. solani, binucleate Rhizoctonia spp., and Cylindrocarpon spp. also were present at this test site and common in strawberry production systems in California . One can infer from the results obtained at the V. dahliae–free Salinas site that rotations with broccoli have benefits beyond the pathogens tested in the current study. In contrast to the reductions in V. dahliae microsclerotia and wilt on strawberry observed in rotations with broccoli and Brussels sprouts, rotations with lettuce resulted in significant increases in V. dahliae microsclerotia and wilt on strawberry. Prior to 1995 , lettuce was not even considered to be a host of V. dahliae, but wilt caused by this pathogen currently is a major problem on lettuce in the central coast of California. Recent studies have clearly established that the strawberry and lettuce strains of V. dahliae belong to the same phylogenetic group based on the sequence similarities of the intergenic spacer region and the combined sequences of the IGS region and the β- tubulin gene. Furthermore, the two strains were also cross-pathogenic to both hosts. Previous molecular profiling based on random amplified polymorphic DNA analysis also concluded that lettuce and strawberry strains displayed the closest phylogenetic relationship relative to the other host-adapted isolates tested . Unlike in most other hosts of V. dahliae, microsclerotia develop along the veins of lower, senescing lettuce leaves prior to plant death and result in abundant augmentation of soil inoculum after an infected crop.

Therefore, it is not surprising that microsclerotia of V. dahliae increased in the soil of lettuce-rotated plots and resulted in higher severity of Verticillium wilt on strawberry and reduced fruit yield compared with other rotations. Residues of other Brassica spp. have proven effective in reducing several other soilborne pathogens . Keinath reported significant reductions of gummy stem blight of watermelon in soil amended with cabbage residue. Chan and Close demonstrated the control of Aphanomyces root rot from Brassica residue amendments. Brassica spp. are well known for their characteristic sulfurcontaining compounds, known as glucosinolates, and for the disease-suppressive effects of the toxic byproducts derived from the breakdown of these compounds . Although this may explain, in part, the successful use of broccoli residues to reduce the number of microsclerotia in soil, other factors also may play an important role in the suppressive effects of Brassica spp. in general. Shetty et al. found that, despite the apparent lack of foliar symptoms and few root symptoms, broccoli roots still were colonized by V. dahliae to the same degree as cauliflower, except when soil microsclerotia levels were high. Under high soil inoculum density, the colonization rate of cauliflower roots was about 1.5-fold higher compared with broccoli roots. Microsclerotia never developed within broccoli root tissues, even 60 days after decapitating plants at the crown. In addition, there was no apparent inhibition of growth of V. dahliae on a medium with broccoli root extracts. This led to the hypothesis that perhaps the reduction in V. dahliae soil populations was caused by the combined effects of broccoli acting as a trap crop to force the germination of microsclerotia and the activation of resident microflora with an ability to degrade lignin-rich broccoli residue in addition to the melanized microsclerotia of V. dahliae . Fungal ligninases have been found to have activity against melanin as well, but microorganisms with melanolytic activity also may be involved . Data from broccoli-rotated plots demonstrated a 1,000-fold increase in bacterial and 100-fold increase in actinomycete populations relative to the unamended control or cauliflower-rotated plots, bato bucket suggesting a biological basis for the suppression of V. dahliae . It also is possible that the reduction in V. dahliae soil populations is partly due to oxygen depletion, created by the increased microbial activity from the incorporated broccoli residue, or from increases in anaerobic activities induced within the oxygen-depleted environment. Blok et al. determined that broccoliamended or rye grass-amended soils covered with a plastic cover created anaerobic environment sufficient to reduce soil inoculum of V. dahliae, Fusarium oxysporum f. sp. asparagi, and R. solani. In contrast, Subbarao et al. found that the effects of incorporated broccoli residue were identical in both open and plasticcovered plots. Perhaps the differences in these two studies can be attributed to the quantity of broccoli residue incorporated and the different field soils. In addition to the effects of glucosinolates on plant pathogens, there may be impacts on the broader soil microbial community, perhaps favoring beneficial organisms. Other studies also have attributed a biological basis of pathogen suppression from Brassica residues or by other means in naturally suppressive soils. Suppression of take-all in wheat caused by Gaeumannomyces graminis in acidic soils was associated with fungal antagonism by Trichoderma spp. . Smith et al. failed to observe changes in microbial communities by Brassica tissues when the following crop was wheat. In in vitro studies , Trichoderma spp. were tolerant to isothiocyanates while Aphanomyces, Gaeumanomyces, and Phytophthora spp. were sensitive, suggesting both a direct suppression from the toxicity of isothiocyanates and favoring of antagonism by Trichoderma spp. The effects of Brassica residues on Pythium propagules in soil have been variable. Stephens et al. reported that mustard tissue incorporation decreased grapevine establishment in soils with high numbers of Pythium propagules. Similarly, Walker and Morey found that, in citrus orchards, the number of Pythium propagules in soil as well as in the root systems were increased by mustard and rapeseed tissue amendments.

Although P. sulcatum and P. violae were highly sensitive to isothiocyanate from Brassica residues, the highly pathogenic P. ultimum was tolerant . In a recent study, Brassicaceae seed meals  stimulated Pythium populations in certain soils whereas B. juncea alone had no effect. In combination with B. napus, however, B. juncea eliminated the stimulation of resident Pythium spp. typically observed when B. napus seed meal was applied alone. Furthermore, elevated populations of Pythium spp. in S. alba or B. napus seed meal-treated soils contributed to significant weed suppression. This weed suppression was lost when Ridomil -methoxyacetylamino]-propionic acid methyl ester was applied to B. napus-treated soil and significantly diminished in S. alba-treated soils, confirming that the high Pythium numbers contributed to weed suppression . In the current study, incorporation of broccoli, Brussels sprouts, cauliflower, or lettuce residues did not alter the total Pythium populations in soil. Because the pathogenic Pythium spp. were not quantified separately, the possibility that incorporation of residue from various crops had some effect on this segment of Pythium population could not be ruled out. The impact of diseases or methods to ameliorate diseases in strawberry is ultimately measured by their effect on yield. As expected, the fumigated control provided the highest yield and correspondingly the highest profits. Even though none of the rotations equaled the level of pathogen and disease suppression observed in the fumigated control, strawberry yield in broccoli-rotated plots was a close second. The unique cost-benefit analysis employed in this study also supported this conclusion. Despite giving up yearly strawberry cultivation that is practiced in some commercial strawberry fields, rotations with broccoli and, to some extent, Brussels sprouts would be a profitable, environmentally friendly method of managing Verticillium wilt in strawberry that is effective in both conventional and organic strawberry production systems. The geometries and topologies of leaves, flowers, roots, shoots, and their arrangements have fascinated plant biologists and mathematicians alike. As such, plant morphology is inherently mathematical in that it describes plant form and architecture with geometrical and topological techniques. Gaining an understanding of how to modify plant morphology, through molecular biology and breeding, aided by a mathematical perspective, is critical to improving agriculture, and the monitoring of ecosystemsis vital to modeling a future with fewer natural resources. In this white paper, we begin with an overview in quantifying the form of plants and mathematical models of patterning in plants. We then explore the fundamental challenges that remain unanswered concerning plant morphology, from the barriers preventing the prediction of phenotype from genotype to modeling the movement of leaves in air streams. We end with a discussion concerning the education of plant morphology synthesizing biological and mathematical approaches and ways to facilitate research advances through outreach, cross-disciplinary training, and open science. Unleashing the potential of geometric and topological approaches in the plant sciences promises to transform our understanding of both plants and mathematics. The study of plant morphology interfaces with all biological disciplines . Plant morphology can be descriptive and categorical, as in systematics, which focuses on biological homologies to discern groups of organisms . In plant ecology, the morphology of communities defines vegetation types and biomes, including their relationship to the environment. In turn, plant morphologies are mutually informed by other fields of study, such as plant physiology, the study of the functions of plants, plant genetics, the description of inheritance, and molecular biology, the underlying gene regulation .

According to the FDA, “Generally, domestic and foreign food facilities that are required to register with Sect. 415 of the Food, Drug, & Cosmetic Act must comply with the requirements for risk-based preventive controls mandated by the FDA FSMA as well as the modernized Current Good Manufacturing Practices of this rule ”. Traditionally, the conventional seafood industry is regulated by the FDA, except for catfish , which along with meat products are regulated by USDA. Cell-cultivated seafood production is considered a novel or alternative food production system. Thus, labeling is also an important part of the regulations for food products. Developing a common terminology to increase transparency is required for clean labeling. There was a comprehensive study for seafood products indicating that two “common or usual names,” “Cell-cultivated Seafood” and “Cell-Cultured Seafood,” met regulatory criteria. By displaying these two phrases on packages of frozen Atlantic Salmon, both “Cell-cultivated” and “Cell-Cultured” enabled participants to differentiate cell-cultivated seafood from “Farm-Raised” and “Wild-Caught” fish. There is a need to develop reliable test kits and rapid detection sensors to validate the safety of cell-cultivated seafood products. Testing methods are essential for assessing allergenicity in seafood products, blueberry packaging containers including those produced through cellular aquaculture. These methods need to encompass not only the cultured cells themselves but also the biomaterial scaffolds employed in the process. In silico assessments can determine sequence homologies and identify structural similarities of newly expressed proteins to existing allergenic examples while other testing methods approved by the EFSA and the FDA for allergenicity verification include the pepsin resistance test and immunochemical crossreactivity testing with Immunoglobulin E from the serum of allergic individuals.

Traceability of cell-cultivated seafood will also be a major topic as is the case with conventional meat products. The conventional seafood industry is highly fragmented with very little connection from the point of harvest to the point of consumption. In contrast, cell-cultivated seafood could be easily traced back to the source of production.One concern with cell-cultivated seafood is that in the future, by developing this novel food production system, the declining need for animals, including fish and crustacea, could negatively impact the fishing industry and the associated communities. However, cell-cultivated seafood is strategically positioned to complement traditional methods like wild-caught species and aquaculture farming, to support sustainability of these communities well into the future. Moreover, the capacity to harvest and culture cells from unconventional seafood sources provides new possibilities for these communities, simultaneously enriching food choices available to consumers. Figure 5 summarizes some of the benefits and challenges/ concerns associated with the cell-cultivated seafood industry.Businesses involved in cell-cultivated meat, including seafood, have been gaining significant importance across the globe, reflected in investments of about $2.8 billion since 2016 among 156 companies dedicated to cell-cultivated meat and seafood production. Cell cultivated seafood is an important niche within the cell cultivated protein sector with industrial investment of $896 million for cell-cultivated meat and seafood with many startups and established companies pursuing cell-cultivated seafoods in 2022. This includes companies in the US, Singapore; Europe; Canada; South Africa; Israel, South Korea, Hong Kong and India. The majority of companies are focused on business-to-consumer and business-to business , with fewer companies in the B2B business model space. Supply chain issues of cell-cultivated seafood will also need to be addressed as the market expands. The market potential for cell-cultivated seafood remains an unknown at the early stages, with price being one of the determinants.

Costs are expected to decrease with cheaper ingredients and with scaling, but this has to be demonstrated in the coming years .Cell-cultivated seafood as a technology offers a potentially transformative impact for foods of the future. This is based on the scientific tools now available, coupled with the features of the technology itself. For example, the potential to directly alter cell composition to provide healthier seafood products is compelling . This impact can be further enhanced pending the acceptability of GM-based approaches, where seafood cells can be bio-engineered to provide even further nutritional and perhaps even therapeutic benefits. Food safety can also be greatly enhanced, as shelf life, microbial community, tracking, and overall freshness can potentially be improved, along with a major reduction in antibiotic use. All of these potential benefits remain to be demonstrated as the field moves forward, but the underlying science to achieve such goals is already in place. In addition, improved food security, food access, novel foods and many other future outcomes can be anticipated. Nutrition – Omega-3s and other inputs – Although fish are recognized as one of the best sources of nutritionally-important long-chain omega-3 fatty acids, the source of these compounds is actually the marine algae, bacteria, and protists. Fish consume these organisms either directly or indirectly via other fish or zooplankton, thereby bio-accumulating omega-3 fats in their tissues. The fact that animal cells—including those of fish and aquatic invertebrates—are incapable of synthesizing omega-3 fats de novo means that producers of cell-cultivated seafood will need to acquire appropriate sources of omega-3 fatty acids as ingredients. These sources could include farming of microalgae, precision fermentation, plant molecular farming, or cell free systems. However, this latter strategy has not yet been explored for omega-3 production to our knowledge, and the former three strategies will still require substantial effort before they can be scaled to the levels that may be required to support the cell-cultivated seafood industry.

Cellular engineering approaches could also provide an opportunity to engineer fish cells to synthesize long-chain omega-3 fatty acids. Codon-optimized transgene expression of omega-3 desaturase gene of C. elegans in a fish cell culture and zebrafish model enhanced the conversion of n-6 PUFA to n-3 PUF. This study also illustrated that combined transgene expression of fat-1 and fat-2 enhanced the synthesis of n-3 PUFA. In addition, cellular engineering may provide a potential solution to enhance the accumulation and stability of omega-3 fats. These approaches may include the use of exogenous reactive oxygen scavengers in the media to promote cell proliferation and suppress oxidation processes, as well as genetic modifications to over-express antioxidant genes, such as superoxide dismutase . Furthermore, cellular engineering approaches also enable the design of media compositions to promote the synthesis of omega-3 fats. Other compounds with important impacts on nutrition and organoleptic properties of seafood are also ultimately derived from the diets of aquatic animals. This includes the carotenoid astaxanthin, which is responsible for the color of salmon and shrimp, as well as for protecting membrane lipids from oxidation. As is the case with omega-3 fats, astaxanthin and other compounds that are diet-derived in conventional seafood will need to either be sourced as ingredients for addition to cell cultivated seafood or synthesized by engineered cells. Notably, the U.S. government recently acknowledged the need to “bolster research into alternative feed ingredients for livestock and aquaculture, including plants, algae, or seaweeds, that can enhance or replace feed ingredients”. Marine-derived feed ingredients such as omega-3s and astaxanthin may be a shared need across both conventional and alternative protein production platforms.Cell-cultivated seafood is in its infancy. There is growing research among academic labs, and a growing corporate effort mainly among startup companies worldwide to tackle the increasing consumer demand for seafood. In these early stages, the focus is on cell sources, media optimization and scaffolding, while with time these efforts will mature into scaling production for impact. With scale, pricing will be reduced and availability will increase. The vision is that this emerging approach to cell-cultivated seafoods will offer safer and healthier alternatives for consumers, while enhancing environmental sustainability goals .For this growing industry to reach its potential, government support for research and commercialization efforts will be essential. A report by the UK Foreign, Commonwealth & Development Office and the ClimateWorks Foundation estimated that annual global public spending on R&D and commercialization—including that of plant based proteins, precision fermentation, insects, blueberry packing boxes and cell cultivated meat—would need to increase to a total of US $10.1 billion to unlock the full benefits of alternative proteins. Whereas terrestrial cell-cultivated meat benefits from a strong foundation of biomedical tissue engineering research, and a fairly detailed understanding of mammalian and avian cell biology generally, this is less true for cell-cultivated seafood. Therefore, basic research aimed at understanding piscine and invertebrate cell types, differentiation processes, and metabolic requirements is still needed. Public funding of such research will reduce duplication of effort and provide a strong foundation for commercial efforts, thereby benefiting the field as a whole, everyday consumers, and the planet. Universal in this evolution to grow cell-cultivated seafood as a major option for alternative food for consumers around the world, safety, flavor and texture are paramount. Thus, regulations and methods to properly assess these new foods and to provide tracking will be a foundational need. In total, the potential for this emerging field to transform the seafood that we consume, while providing major benefits to sustainability, quality and food safety are expected to continue to drive the growth of this field. Both fishing and aquaculture already face major environmental challenges, and cell-cultivated seafood offers a new approach to address these issues, while also expanding our palates in ways never before possible. The future is exciting, but the path will need to be built upon a strong scientific foundation linked to consumer willingness to try these new foods and eventually to embrace them.

California has led the nation in farm sales since 1950, when Los Angeles County had more farm sales than any other county in the United States, largely because of specialization in the production of high-value fruit, nut and vegetable crops. California’s farm sales in 2015 were $47 billion, including $18 billion from the sale of fruits and nuts, $9 billion from vegetables and melons, and $5 billion from horticultural specialties such as floriculture, nurseries and mushrooms. That is, $32 billion, or two-thirds, of farm sales were from these FVH crops. The leading farm counties, Tulare, Kern and Fresno, each had farm sales of almost $7 billion in 2015 . The production of many fruits and vegetables is labor-intensive, meaning that labor represents 20% to 40% of production costs for table grapes, strawberries and other commodities. Average employment of 421,300 farmworkers in 2015 represents 12 monthly snapshots of persons on the payroll during the pay period that includes the 12th of the month. However, total wages of $12.8 billion are all wages paid to all workers, including those who were employed at other times during the month and those who earned wages from non-farm employers. A worker who was employed 2,080 hours — the number of hours California’s Employment Development Department considers full-time and full-year employment — would earn an average annual pay of $30,300, which prompted the Los Angeles Times to ask why, despite implied hourly wages of almost $15 per hour, U.S.-born workers reject farm jobs . The answer is that few farmworkers are employed year-round; many are employed fewer than 2,080 hours a year. In 2015, the average earnings of all workers with at least one farm job was $20,500. EDD does not collect hours of work data from employers who are paying unemployment insurance taxes, but does collect the earnings and employment data that we use in this article. The National Agricultural Workers Survey collects hours of work data from California crop workers, and found that they were employed an average of 47 hours during the week before they were interviewed in 2015–16. American Community Survey data, also collected from workers, shows that both crop and livestock workers were employed slightly more than 40 hours a week. The NAWS and ACS do not collect data on annual hours worked. However, if workers averaged more than 40 hours a week over 52 weeks, average hourly earnings would be lower than $15. Non-supervisory production workers do most of the work on the state’s largest farms that produce labor intensive FVH crops. About 90% of California crop workers were born in Mexico, and 60% are unauthorized, according to the NAWS, which is 10 percentage points higher than the U.S. average of 50% unauthorized crop workers . The reason for more unauthorized workers in California is that it has a higher share of foreign-born workers: most foreign born workers are unauthorized, and California’s 90% share of foreign-born crop workers exceeds the 60% foreign-born share in the rest of the United States. The dominance of labor-intensive crops in California, and the Trump administration’s efforts to step up border and interior enforcement, has increased interest in the availability of farmworkers.

Determining how long grape berries are competent to induce the expression of anthocyanin biosynthetic genes may help determine the optimal time, number, and frequency of S-ABA applications. Currently, little is known about the potential benefits of multiple applications, which may be desirable if a single application results in an insufficient response. The aim of the present study was to determine the effects of S-ABA applications at different concentrations and times on the quality and biochemical properties of berries from the seedless grape Selection 21 hybrid during three growing seasons in the region of Paraná, Brazil. We evaluated a variety of parameters including: grape color development, berry phenolic profiles, and gene expression of transcriptional regulators and biosynthetic enzymes of the anthocyanin pathway after treatments with S-ABA. The results of this report indicate that two S-ABA applications during and after véraison extend the competency of grape berries to respond to ABA and induce the accumulation of anthocyanins, resulting in higher grape berry coloration. The study was conducted during three consecutive seasons in a commercial vineyard located in Marialva, state of Paraná , Brazil , using 4-year-old vines of hybrid seedless grape Selection 21 grafted onto IAC 766 Campinas rootstock. According to the Köppen classification, growing bags the climate of the region is Cfa , with an average temperature below 18◦C in the coldest month and above 22◦C in the hottest month and an average annual rainfall of 1,596 mm. The region’s soil is classified as dystroferric red latosol .

The vines were trained using a bilateral overhead trellis system, where vines were spaced at 2.5 m × 2.5 m , and each vine had 6.25 m2 total canopy area. Cane pruning was performed during the 2013, 2014, and 2015 seasons and was followed by application of 3% hydrogenated cyanamide to the two apical buds to induce and standardize sprouting. The number of canes per vine was evenly adjusted to 40 and the number of shoots per vine was also established to 40 . Considering that a grape bunch of the Selection 21 weighs on average 460 g, the load per vine is 18.40 kg, which represents an estimated yield of 29.44 tons/ha. Furthermore, to avoid drifting, a non-treated vine was left as side border between two treated vines, which almost duplicated the experimental area. In each plot, all grape bunches were treated , and the bunch samples were collected from random positions at each side of the canopy to account for intracanopy variability. Control plants were not subjected to any treatment, instead, they were sprayedwith water at the same time and following the same procedures as the S-ABA treatments.The effects of applying S-ABA isomer at different concentrations and times were evaluated in terms of berry quality traits. ProTone R, the commercial growth regulator used in this study, has an active ingredient concentration of 100 g/L S-ABA. As shown in Figure 1, the initial treatments tested in the 2013 and 2014 seasons corresponded to: control or water spray, 200 mg/L S-ABA application at 7 days after véraison , 400 mg/L S-ABA application at 7 DAV, 200 mg/L S-ABA application at 7 DAV plus an additional application at 21 DAV, and 400 mg/L S-ABA at 7 DAV plus an additional application at 21 DAV. In the 2015 season, only the control and treatments of 400 mg/L S-ABA with one or two applications were performed and analyzed.

Berry samples from the 2015 season were collected from each treatment at four different times: 7 DAV , 14 DAV, 28 DAV, and 35 DAV for further targeted analyses . For all seasons, a randomized complete block experimental design was used, with five treatments and three to four replicates, and with each plot consisting of one vine . Véraison was determined by measuring soluble solid content and firmness of grape berries randomly sampled in the experimental vineyard. At véraison, the mean grape SSC concentration was 9◦Bx, and 20% of the berries in more than 50% of the grape clusters presented softening . The berries presented a mean of 11◦Bx at 7 DAV, the time of the first S-ABA application, and a mean of 13◦Bx at 21 DAV, the time of the second S-ABA application. For treatment applications, grape clusters were sprayed in the morning using a knapsack sprayer at a pressure of 568.93 psi with JA1 hollow cone nozzle tips at a volume of 800 L/ha to provide complete and uniform coverage. In addition, 0.3 mL/L of Break-Thru R a non-ionic surfactant was added to all treatments. During the trials, the standard regional cultivation practices with regard to nutrition, weed control, and pest and disease management were used.Clusters of each plot were manually harvested when SSC stabilized . The clusters were cleaned, and damaged berries were discarded. Color coverage of the bunches was determined using 10 grape clusters per plot by visually rating the clusters on a scale of 1–5 using the following scale: 0–20%, 21–40%, 41–60%, 61–80%, and 81–100% coverage .

The same grape clusters used for evaluating color coverage measurements were used for berry sampling. For physicochemical analyses, two berries were collected from the upper, middle, and lower portion of each grape bunch, yielding a total of 70 berries per plot. Total anthocyanins and color index of red grapes were determined in berry samples from all seasons. The following variables were analyzed only for the 2013 and 2014 seasons: color coverage, total polyphenols, and berry firmness. All physiological analyzes were performed in the Laboratory of Fruit Analysis of the Agricultural Research Center, Londrina State University, Brazil. The total anthocyanin concentration of the berries was determined using 30 berries per plot, which were frozen and stored at −20◦C. The berry skins were removed using tweezers, taking care to remove only the skin, without pulp. The skins were washed once with water, followed by washing in deionized water and drying with absorbent paper. A 5-g skin sample was then placed in a polystyrene tube containing 50 mL of acidified methanol and stored in the dark for 48 h at room temperature. The tubes were then removed from the dark and stirred manually for 5 s. Absorbance was determined using a Genesys 10S spectrophotometer at 520 nm with the solvent as blank. The results were expressed in milligram malvidin-3-glucoside per gram of skin . The CIRG was determined using 10 berries per plot with a CR-10 colorimeter , using the CIELAB color system. The following variables were determined for the berry equatorial section: lightness , saturation , and hue . CIRG was then determined using the following equation: CIRG = / . Total polyphenol determination was performed using 30 berries per plot based on a modified Folin–Ciocalteu method. In summary, the absorbance of each sample was measured after 15 min at 765 nm using a Genesys 10S spectrophotometer against a blank sample prepared with water instead of the extract. Determination of total polyphenol was calculated from the calibration curve obtained with gallic acid. The results were expressed in milligram total polyphenols per 100 g of sample . The berry firmness was performed with a TA.XT2i Texture Analyzer , at 25 ± 1 ◦C, nursery grow bag analyzing the equatorial position of 10 berries with pedicels per plot. Each berry was placed on the base of the equipment and compressed using a cylindrical probe with a diameter of 35 mm parallel to the base. A constant force of 0.05 N at a speed of 1.0 mm/s was applied to promote the cracking of the sample. The berry firmness was then determined .Application of abscisic acid increased the total anthocyanin concentration in berry skins of the seedless grape Selection 21 during the 2013 and 2014 seasons, regardless of the S-ABA concentration and time of application . However, berries that received 400 mg/L of S-ABA at 7 and 21 DAV had significantly higher, almost two to three times more, anthocyanin concentrations than other treatments. According to the CIRG, berries from control treatments had a green to a yellow color in both seasons . In 2013, berries treated with one or two applications of 200 mg/L S-ABA or one application of 400 mg/L S-ABA at 7 DAV, and those in the 2014 season that were treated with one application of 200 mg/L S-ABA developed a pink color . Remarkably, berries of the 2013 season treated with two applications of 400 mg/L S-ABA and berries of the 2014 season treated with one or two 400 mg/L S-ABA applications, developed a stronger red color .

For both the 2013 and 2014 seasons, color coverage was lowest in control grapes and highest in grapes treated with two applications of 400 mg/L S-ABA. Increase in total polyphenols was evident in grapes subjected to two 400 mg/L S-ABA applications during the 2013 and 2014 seasons. These berries also presented the lowest mean berry firmness . Importantly, the increased softening due to S-ABA application did not result in higher frequency of cracked berries in any of the studied seasons. Qualitative assessment of berry cracking was performed visually. Further analyses of the effect of 400 mg/L S-ABA treatments on CIRG, total and individual anthocyanins concentrations, and gene expression of transcription factors and biosynthetic enzymes were performed with grape berries collected from the 2015 trial. Measurements of CIRG confirmed previous results obtained during the 2013 and 2014 seasons, at the time of harvest , grapes treated with two S-ABA applications had the highest CIRG values . Grape bunches from the control treatment presented pink berries , whereas those treated with one or two applications of S-ABA had red berries . As determined in the previous seasons, berries treated with 400 mg/L S-ABA also presented higher total anthocyanin content than the control at 14 and 28 DAV . At 28 DAV, grapes treated with one or two applications of 400 mg/L S-ABA presented total anthocyanin concentrations almost three times higher than the control. Even 3 weeks after the first application , berries treated with only one S-ABA application showed a total anthocyanin content similar to those treated with two S-ABA applications. Nonetheless, the second application of 400 mg/L S-ABA significantly affected the total anthocyanin accumulation at the time of harvest . S-ABA altered the concentrations and proportions of individual anthocyanins in berries from the seedless grape Selection 21 . With the exception of petunidin- 3-glucoside, S-ABA application significantly improved the concentrations of all the measured anthocyanins. Cyanidin-3- glucoside and peonidin-3-glucoside levels increased at 14 DAV, 1 week after the first S-ABA application. The second S-ABA application stimulated the accumulation of the anthocyanin delphinidin-3-glucoside at 28 DAV, yielding differences relative to both the control and to the samples treated with only one S-ABA application. At 28 DAV, the concentrations of peonidin-3-glucoside and malvidin-3-glucoside increased after exogenous S-ABA application but were not further increased by the second application. At the time of harvest , peonidin-3-glucoside and cyanidin-3-glucoside were the dominant pigments present after all treatments. Delphinidin- 3-glucoside, cyanidin-3-glucoside, and peonidin-3-glucoside presented higher accumulation following the second application of 400 mg/L S-ABA, but the number of applications did not affect the accumulation of malvidin-3-glucoside. As presented in Figure 4, treatment with 400 mg/L S-ABA significantly increased the expression of the transcription factors VvMYBA1 and VvMYBA2 and the expression of the bio-synthetic genes CHI, F3H, DFR, and UFGT 1 week after the first application . Three weeks after the first S-ABA application , expression of CHI, F3H, and DFR genes remained high, but this was not observed for the transcription factors VvMYBA1 and VvMYBA2 or the UFGT gene. Four weeks after the first S-ABA application , no significant differences were observed in the expression of genes or transcription factors between berries that received one S-ABA application and those that received the control treatment. The two applications of 400 mg/L S-ABA induced expression of the genes CHI, F3H, DFR, and UFGT and the transcription factors VvMYBA1 and VvMYBA2 at 14 and 28 DAV . F3H expression was the most affected by S-ABA application, displaying higher levels than the control until the final stages of berry maturation at 35 DAV,whereas the remaining genes presented no differences from the control at harvest. Overall, the gene expression results indicate that a second S-ABA application contributed to the maintenance of the expression of the transcription factors VvMYBA1 and VvMYBA2 and the genes F3H and UFGT at higher levels than in the control for an extended period of time.

Although string connections did increase ant resource recruitment efficiency and pest removal rates compared to the control treatments, A. sericeasur exhibited a clear preference for natural vegetation over string connections. Interestingly, while distance from the A. sericeasur nest tree did negatively impact ant activity, recruitment to baits, and ant-mediated CBB removal on the control and string treatments, distance did not affect these response variables on the vegetation treatment plants. Vegetation connectivity influences the distribution, diversity, and interspecific competition of arboreal ant species by affecting the availability of nesting habitats, foraging ranges, and resource availability. Higher degrees of vegetation connectivity provide a range of food resources to arboreal ants, including access to honeydew-producing insects, extrafloral nectaries, and other insects. Arboreal ants can take advantage of these resources more efficiently when connected vegetation provides a network of foraging opportunities, which increases access to patchy resources while enhancing predator avoidance capability. In contrast, disconnected vegetation may limit ant distribution to isolated tree patches. Observed increases in ant activity on plants with vegetation connectivity suggest that structural connectivity facilitates ant mobility and movement efficiency on foraging paths. Between the control, string, and vegetation treatments, ant activity was highest on vegetatively connected plants . After string placement, ant activity did increase on the string plants, indicating that A. sericeasur learned to use strings as foraging paths over time; however, nusery pots the overall ant activity levels on the string treatment plants were not significantly different from the control treatment.

The significant positive interaction between the string treatment and time explains the observed increase in ant activity on the string treatment plants. On the control and vegetation treatment plants, there was no change in ant activity throughout the 5-week duration of the experiment. Consistent with Jiménez-Soto et al., ant activity decreased on coffee plants with increasing distance from A. sericeasur nest trees on the control and string plants. Notably, our additional treatment of naturally occurring vegetation connectivity overrode the effect of distance from ant nest trees, with no impact of distance on the amount of ant activity on the vegetation treatment plants. This important finding suggests that vegetation pathways can facilitate A. sericeasur foraging activity on coffee plants that are farther away from their nest tree. Additionally, increasing their foraging range may help the ants to avoid parasitic phorid flies in the genus Pseudacteon, which parasitize A. sericeasur and decrease in density with increasing distance from the A. sericeasur nests. A. sericeasur activity may be highest on coffee plants with naturally occurring vegetation connections because vegetation connections are generally larger and more structurally complex. Additionally, on the existing vegetation pathways, the ants had more time to establish foraging trails and chemical cues as compared to the string connections. Furthermore, in addition to providing linear foraging trails, vegetation bridges may also contain useful resources including extrafloral nectaries and plant fluids that the strings do not provide. Vegetation pathways can also offer protection from phorid flies beneath the leaves, whereas strings are open and unprotected foraging paths. Studies have also suggested that ants have preferences for foraging on certain surfaces, and that surface characteristics impact foraging speed and chemical communication on the ants’ trails.

The A. sericeasur preference for vegetation surfaces may therefore result from texture-based foraging efficiency differences between vegetation and string. Yanoviak et al. studied ant recruitment to baits on bare vs. moss-covered tree trunk surfaces and observed the Azteca spp. actively avoiding baits on moss-covered trunks, indicating a clear surface preference for smoother pathways. In our study, we observed A. sericeasur walking around stray threads on the jute strings , decreasing their foraging efficiency compared to smoother thread-free vine surfaces. In some instances, we observed A. sericeasur “cleaning” the string pathways by biting off jute string threads from the connections to minimize obstacles and enhance their efficiency on these pathways. Another explanation for higher A. sericeasur activity on the vegetation treatment coffee plants is that A. sericeasur may already be tending established green scale colonies on vegetatively connected plants, drawing their activity to these plants over the string treatment plants. C. viridis, a sessile coffee scale insect, has been linked to increased A. sericeasur activity. In a mutualistic relationship, A. sericeasur protect C. viridis from predation in exchange for the honeydew that these scales produce. Increased connectivity, by increasing ant mobility, may also increase the scale tending activity by A. sericeasur. Notably, interactions between A. sericeasur and CBB on coffee plants occur more frequently with higher densities of C. viridis, indicating a relationship between scale tending activity and CBB control services.Consistent with the ant activity results, the number of ants recruiting to baits on control and string plants declined with distance from the ant nest tree but remained consistent over all distances for vegetation treatment plants. These results confirm the A. sericeasur preference for vegetation foraging paths over artificial ones, as explained in Section 4.1.

Between treatments, the control treatment plants had the lowest ant recruitment to baits. Other ants in tropical systems similarly prefer vegetation pathways over ground and leaf litter, optimizing networks of vines, leaves, and branches in their foraging trails. Clay et al. suggest that ants may even favor vines over bark or moss because the linear nature of vines reduces the necessity for intensive chemical trail maintenance. Strings might similarly provide this linear path advantage, which reduces chemical trail maintenance and opportunities for path confusion compared to ground trails. Because ants account for energy efficiency when deciding between foraging paths, the control plant baits were likely the least attractive because they required the highest energy expenditure due to traveling over ground and leaf litter. Because none of the tuna baits were depleted within the 20 min observation period, recruiting to control baits while more energy-efficient paths were present is an inefficient use of ant workforce.Over time, the overall number of ants that recruited to the baits decreased with time post-string placement on both the control and vegetation plants, but there was no significant change in the number of ants that recruited to the baits on the string treatment. Decreases in ant recruitment rates on the control and vegetation treatment plants may have resulted from the presence of phorid flies, plastic planters which greatly reduce A. sericeasur activity. Phorid fly attacks may have curtailed ant recruitment along the pre-existing foraging routes, as phorids are likely more abundant in leaf litter along popular foraging routes. Because the strings were a novel foraging route, it is likely that fewer phorids frequent those routes and interfere less with ant recruitment to the baits. Between treatments, A. sericeasur removed the most CBB from vegetation treatment plants and removed more CBB on the string plants as compared to the control plants . The overall number of CBB removed on the vegetation plants decreased with time post-string placement. Decreases in CBB removal may similarly have resulted from phorid fly attacks inhibiting pest removal activity, as occurred in Philpott et al. and Pardee and Philpott. Consistent with the results of our ant activity and resource recruitment experiments, the number of CBB removed on the control and string plants declined with distance from the nest tree, but remained consistent with distance from the nest on the vegetation treatment plants. Interestingly, Jiménez-Soto et al. did not find any effect of distance from the nest tree on CBB removal for the control or string plants. Our contrasting results may be the result of the A. sericeasur preference for the vegetatively connected plants in our study; in the absence of vegetation pathways, ants may forage more on artificial connections. Our results reinforce how habitat complexity in the form of vegetation connectivity impacts interspecific interactions, specifically ant-mediated CBB removal at the local scale.Our results confirm the importance of naturally occurring vegetation connectivity and habitat complexity in facilitating arboreal ant mobility and ant-mediated CBB removal. Our findings have important implications for the practical application of ant-provided pest removal in coffee systems, indicating that A. sericeasur may most effectively control CBB on coffee plants with natural vegetation connectivity connected to their nest trees. In the absence of vegetation connectivity, implementing artificial connections between ant nests and coffee plants can increase CBB removal by A. sericeasur; however, with increasing distance from the ant nest tree, the strength of this pest removal service decreases on artificially connected plants. The observed preference of A. sericeasur for vegetation pathways underscores the importance of maintaining or promoting vegetation connectivity via habitat complexity and structural diversity within coffee agroecosystems. In managing agroecosystems in support of ant-mediated ecosystem services, artificial connectivity does not provide an equal substitute for the naturally occurring vegetation connectivity provided through forest conservation and structural complexity. Consistent with studies affirming the influence of vegetation connectivity on predatory arthropod movement and predation range, our results illustrate how vegetation connectivity facilitates A. sericeasur foraging mobility and pest removal. In coffee systems, higher degrees of vegetation connectivity are associated with shade trees, as well as more heterogeneous habitat complexity and variability in plant structure.

In other studies, ants generally increase predation services in shaded systems as compared to monocultures and, in coffee plants, more effectively remove CBB in shaded coffee systems as compared to sun monoculture systems. Interestingly, most studies find the opposite effect of structural complexity on parasitoid behavior, with higher degrees of plant structural complexity leading to decreased parasitoid foraging efficiency. This negative relationship between parasitism and habitat complexity transfers to coffee systems, where the parasitic phorid flies exert a greater inhibiting effect on Azteca ants in simple, low-shade farms thanin complex, high-shade farms. Together with the aforementioned study, our combined results illustrate how habitat complexity at the landscape scale and vegetation connectivity at the plot scale dually facilitate A. sericeasur-mediated pest removal: by facilitating ant mobility and by reducing the efficiency of the parasitoid that interferes with their pest removal ability. In order for A. sericeasur to provide ant-mediated pest removal services, coffee agroforests must include enough shade trees to provide sufficient habitats for ant nests. Planting coffee plants close enough to shade trees to allow for direct connectivity and leaving some vegetation connections between coffee plants and shade trees rather than chopping them or relying on herbicides can facilitate ant-provided ecosystem services by providing foraging paths through naturally occurring structural connectivity. By enhancing the A. sericeasur effectiveness in controlling CBB populations, vegetation connectivity can potentially reduce chemical pesticide use. Our results offer management insight into one piece of a complex ecological puzzle. Because A. sericeasur tend C. viridis, they could indirectly reduce coffee plant growth by contributing to high-scale densities and an associated damaging sooty mold. However, high densities of C. viridis also beneficially attract Lecanicillium lecanii, which attacks coffee leaf rust, a devastating coffee fungal disease. Moreover, the CBB is regarded as a far more damaging coffee pest than C. viridis. Furthermore, facilitating the mobility of A. sericeasur as a single ant species is not necessarily the most effective pest management approach, as higher ant diversity can improve pest control through the cooperation of complementary predatory species. Enhanced A. sericeasur activity on coffee plants could alter the behavior of other ant species, which could have positive or negative effects on overall pest control services due to spatial complementarity or potential negative interactions between predators. However, studies find that increasing connectivity generally increases species richness, and so, vegetation connections that increase A. sericeasur mobility likely facilitate the mobility of other predatory ants in coffee systems, even by providing alternative paths to avoid aggressive altercations with A. sericeasur. Although A. sericeasur occupies only 3–5% of the shade trees at our research site, other ants known to contribute to CBB regulation would likely also use vegetation pathways, facilitating additional pest control. Future research should examine how vegetation connectivity impacts the abundance and diversity of other ant species on coffee plants and the associated spatial complementarity between specific predators of the CBB. Future studies could also investigate how phorid attacks on Azteca vary on different foraging pathways to better understand the mechanisms behind their preference for vegetation pathways. The earliest cultivars of allo-octoploid garden strawberry originated approximately 300 years ago from spontaneous hybrids between ecotypes of non-sympatric wild octoploid species: Fragaria chiloensis subsp. chiloensis from South America and Fragaria virginiana subsp. virginiana from North America.

Nematicides have been commonly used to control PPNs in agriculture, but some nematicides such as methyl bromide and aldicarb are currently banned from use in many countries due to their negative effects on the environment and human health . It has therefore become important to understand the molecular mechanisms of plant immunity against PPNs to provide a foundation for the development of new environmentally friendly and effective control methods. In general, the plant immune system is represented by two inter-related tiers . The first is governed by cell surface-localized pattern recognition receptors that perceive pathogen associated molecular patterns , leading to pattern triggered immunity . Successful pathogens secrete effector molecules into the apoplast ordirectly into plant cells, which interfere with PTI, resulting in successful infection. Resistant plants recognize cell-invading effectors through recognition by intracellular nucleotide-binding domain leucine-rich repeat -type immune receptors, which are encoded by resistance genes. Similar mechanisms are also conserved in plant-PPN interactions. For example, the well conserved nematode pheromone ascaroside has been identified as a PAMP , but the corresponding PRR has not yet been found. PPN genome sequence analyses identified a number of candidate virulence effectors , and a handful of NLR protein-encoding R genes involved in PPN recognition have been well-studied and characterized, including tomato Mi-1.2, Mi-9, and Hero-A; potato Gpa2 and Gro1-4; pepper CaMi; and prune Ma . Mi-1.2, Mi-9, CaMi, and Ma confer resistance against RKNs, black flower buckets whereas Hero-A, Gpa2, and Gro1-4 provide resistance against CNs.

Although the PPN perception mechanism is somewhat clearer at the molecular level, it is still largely unknown what kind of downstream responses are induced after the recognition of avirulent PPNs. It is also unclear what kind of host responses are induced after infection with virulent PPNs, leading to susceptibility and infestation. There are several difficulties in working on plant responses against PPNs. First and foremost, most model plants, such as Arabidopsis, are susceptible to PPNs and therefore cannot be used to study the cascade of responses leading to resistance. Second, PPNs migrate long distances inside roots, inducing complicated responses as they go, triggered by mechanical stress and wounding, among others, making it difficult to pinpoint the key genes involved in resistance or susceptibility by transcriptome analyses. Some studies have used comparative transcriptomics using susceptible and resistant plants infected with a single genotype of nematode . However, it is difficult to rule out the possibility that differences in gene expression were due to resistance or susceptibility rather than to differences in the genetic backgrounds of host plants. Lastly, susceptible responses such as the formation of feeding sites are induced in specific cells targeted by PPNs, and defense responses are likely to be induced in the cells directly impacted by PPN activity. Thus, cells responding to PPNs are rather limited, making the analysis technically challenging. Here we have introduced Solanum torvum Sw “Torvum Vigor” to overcome these problems. S. torvum has been widely used as a rootstock of eggplant to prevent disease caused by PPNs, as well as the soil-borne pathogens Ralstonia solanacearum, Verticillium dahliae, and Fusarium oxysporum f. melongenae n. f. . S. torvum Sw “Torvum Vigor” is resistant to Meloidogyne arenaria pathotype A2-O , but susceptible to M. arenaria pathotype A2-J .

By using S. torvum and avirulent or virulent isolates, we established an in vitro infection system and performed comparative transcriptome analyses to identify genes whose expressions were associated with either resistance or susceptibility by carefully collecting only root tips attacked by RKNs, which allowed us to detect gene expression only in cells directly affected by nematodes. In addition, observation of infected root tip morphology suggests that the success or failure of the immune system against PPNs is determined within a few days of invasion. Thus, we decided to focus on the transcriptional changes that occurred in the very early stages of infection, which has not been studied in previous transcriptomic analyses . Comparative clustering analyses of gene expression identified a large number of novel genes, especially those involved in susceptibility through cell wall modification and transmembrane transport; resistance through lignin and isoprenoid biosynthesis and fatty acid metabolism; and suberin biosynthesis in mechanical wounding. Consistent with the transcriptional up-regulation of lignin biosynthetic genes from A2-O invasion, lignin is accumulated at the root tip of S. torvum infected with avirulent A2-O but not with virulent A2-J, suggesting that S. torvum reinforces the cell wall as a defense response against the avirulent RKN. M. arenaria pathotypes A2-J and A2-O were propagated on Solanum lycopersicum cultivar “Micro-Tom” in a greenhouse. Nematode eggs were isolated from infected roots and then hatched at 25 ◦C. Freshly hatched J2s were collected and transferred to a Kimwipe filter placed on the top of a glass beaker filled with sterilized distilled water containing 100 µg/ml streptomycin and 10 µg/ml nystatin. Only active J2s pass through the filter. Filtered J2s were surface sterilized with 0.002 % mercuric chloride, 0.002 % sodium azide, and 0.001 % Triton X-100 for 10 min, and then rinsed three times with SDW . Eleven-day-old S. torvum seedlings grown on the MS-Gelrite in 6-well plates were inoculated with 200–300 J2s resuspended in SDW.

The plates were wrapped in aluminum foil for 2–3 days after inoculation to promote nematode infection. When mature giant cells were observed 18 days post-inoculation , we used the MS-Gelrite media without sucrose to prevent the formation of callus-like structures. The difference in the number of normal galls formed by A2-J or A2-O at 4 DPI was statistically tested using the Mann-Whitney U test with R software . Nematodes resident in root tissues were stained with acid fuchsin 2–4 DPI , photographed by light microscopy , and the photomicrographs were processed using cellSens . For the observation of giant cells and developing nematodes at 18 DPI, infection sites were fixed with glutaraldehyde and cleaned with benzyl-alcohol/benzyl-benzoate . We observed BABB-cleaned samples by confocal laser scanning microscopy . Photomicrographs were processed using LAS X software . S. torvum seedlings were grown on half-strength MS-Gelrite medium containing 1% sucrose. Eleven-day-old seedlings were treated with SDW as a mock infection or with 200–300 J2s of M. arenaria A2-J for susceptible infection or A2-O for resistant infection. Root tips attacked by the nematodes were checked under microscopy, and more than 50 root tips were cut and collected for each treatment . Root tip samples were collected at 1, 2, and 3 DPI with four biological replicates. Whole shoot and root samples were collected at 1, 3, 6, and 9 DPI with four biological replicates. Root tip samples were used for de novo assembly and differential gene expression analyses, and whole shoot and root samples were used only for de novo assembly. RNA-seq libraries were prepared from the collected samples using a high-throughput RNA-seq method . The 85-bp paired-end reads for the root tip samples, and the 85-bp single-end reads for the whole shoot and root samples were sequenced on an Illumina NextSeq 500 platform . The FASTX toolkit 0.0.13.2 was used for quality filtering. Low-quality nucleotides were removed from the 30 ends, french flower bucket and short reads were excluded. Reads with at least 95% of nucleotides with Phred scores > 20 were kept and used for the downstream analyses . Filtered reads were mapped to the genome assembly of M. arenaria A2-J or A2-O using HISAT2 to exclude reads of nematode origin. Unmapped reads were used for de novo transcriptome assembly . Three different transcriptome assemblers were used for de novo assembly: SOAPdenovo-Trans v1.03 , Velvet v1.2.10 /Oases v0.2.09 and Trinity package v2.4.0 . Unmapped paired-end and single end reads were normalized using Trinity and assembled independently . Oases assembled scaffolds were split at gaps into contigs before merging with contigs from the other assemblies with the EvidentialGene tr2aacds pipeline. The tr2aacds pipeline produces ‘primary’ and ‘alternate’ sequences of non-redundant transcripts with ‘primary’ transcripts being the longest coding sequence for a predicted locus. Next, we used the evgmrna2tsa program from EvidentialGene to generate mRNA, coding, and protein sequences. BUSCO v3.0.2 was applied for quantitative assessment of assembly completeness. This assembly and one previously reported for S. torvum by Yang et al.were compared to the Embryophyta odb9 dataset, which contains 1,440 BUSCO groups. The homology of the contigs from the final assembly was searched against the NCBI non-redundant database using BLASTX with an e-value threshold of 1E-05.

We also compared the contigs with Arabidopsis genome annotation  using BLASTX at the e-value cutoff of 10. Results of the annotation are summarized in Supplementary Table 2. To group genes by expression pattern, we applied the self organizing map clustering method on genes within the top 25 % of the coefficient of variation for expression across samples as previously described . Scaled expression values, representing the average principal component values among each gene in a cluster were used for multilevel three-by-three hexagonal SOM . The final assignment of genes to winning units formed the basis of the gene clusters. The results of SOM clustering were visualized in a principal component analysis space where PC values were calculated based on gene expression across samples . We compared the contigs of our assembly with the NCBI non-redundant database using BLASTX with an e-value threshold of 1E-05. In addition, predicted amino acid sequences that begin with methionine were also annotated using InterProScan . BLASTX and InterProScan outputs were used for Blast2GO analysis to annotate the contigs with Gene Ontology terms . GO enrichment analyses of the sets of genes induced by A2-O infection at 1 DPI or that were assigned to each cluster generated by SOM was performed by comparison with all genes using GO terms generated by Blast2GO at the FDR cutoff of 1E-04 . We further used the “Reduce to most specific terms” option in Blast2GO to remove general GO terms and obtain only the most specific GO terms.Quantification of aliphatic suberin was performed as described previously . Eleven-day-old plants were treated with SDW or infected with A2-J or A2-O. At 4 DPI, root tips inoculated with nematodes were microscopically checked for infection, and more than 50 infected root tips were cut and collected for each treatment. To remove unbound lipids, samples were extracted in methanol for 24 h then in chloroform for 24 h, dried, and weighed. Samples were depolymerized and analyzed by gas chromatography-mass spectrometry for monomer identification and for quantitative analysis based on an internal standard using an identical gas chromatography system coupled with a flame ionization detector as described previously . To understand the differential responses of S. torvum to M. arenaria A2-J and A2-O, we first established an in vitro infection system. Seedlings of S. torvum were grown in MSGelrite plates for 11 days and then inoculated with 200–300 J2s of A2-J or A2-O. At 4 DPI, more than 90 % of root tips infected with A2-J induced the formation of gall-like structures ranging in size. These galls are classified here as “normal” galls, while the rest produced brown pigments. Normal galls lacked obvious brown pigment accumulation and were further classified based on the width of the gall into small , medium , and large . In contrast, about 60 % of A2-O-infected root tips accumulated at least some brown pigment. Some of these brownish root tips also had an abnormal appearance due to the formation of balloon-like structures, and others had many localized and highly pigmented spots. There were a very few small gall-like structures formed after infection with A2-O, but far fewer and smaller than in root tips infected with A2-J . RKN staining by acid fuchsin revealed that both A2-J and A2-O successfully invaded the roots . Interestingly, host cells invaded by A2- O uniformly accumulated brownish pigments, suggesting that the surrounding tissue is strongly responding to, and highly correlated with A2-O infection, a response that was absent from A2-J infected roots. It is generally known that browning of plant tissue is related to enzymatic or non-enzymatic oxidation of phenolic substances , but the identity of the brown pigments synthesized upon infection with A2-O is unknown. By 18 DPI, A2-J had induced the formation of mature multinucleate giant cells and developed into fourth stage juveniles . In contrast, A2-O did not induce the formation of giant cells nor develop past second stage juveniles.