The plants for our experiments were artificially inoculated with race 1 or 2 isolates of F. oxysporum f. sp. fragariae using previously described protocols . The AMP132 isolate originated in California, whereas the MAFF727510 isolate originated in Japan . To produce spores, the pathogen was grown on potato dextrose agar or Kerr’s broth under continuous fuorescent lighting at room temperature, as previously described . Crude suspensions were passed through two layers of sterilized cheesecloth to remove hyphae. Spore densities were estimated using a haemocytometer and diluted with either sterile DI water or 0.1% water agar to a final density of 5 × 106 spores/ml. Seedling and bare-root plants were inoculated by submerging their root systems up to the crown in the spore suspension for 7–8 min prior to planting. The individuals in these studies were visually phenotyped for resistance to Fusarium wilt over multiple post-inoculation time points using an ordinal disease rating scale from 1 to 5 . For our field studies, individual plants were phenotyped once per week for four to eight consecutive weeks beginning in early June. Symptoms were observed on plants 26- to 36-weeks post-inoculation. For greenhouse and growth chamber studies, entries were phenotyped weekly for 6 to 12 weeks post-inoculation. For field, greenhouse,square black flower bucket and growth chamber experiments, the onset and progression of disease symptoms among resistant and susceptible checks were used as guides for initiating and terminating phenotyping.Our race 1 resistance screening experiments were conducted over a three year period at the UC Davis Plant Pathology Farm. The plants for these experiments were artiificially inoculated with the AMP132 isolate of the pathogen. Strawberries had not been previously grown in the fields selected for our studies.

The fields were tilled and disked prior to fumigation and were broadcast fumigated in October of each year with a 60:40 mixture of chloropicrin:1,3-dichloropropene at 560.4 kg/ha. The entire field was sealed with an impermeable plastic film for one-week post-fumigation before shaping 15.3 cm tall × 76.2 cm center-to-center raised beds. Sub-surface irrigation drip tape was installed longitudinally along the beds followed by black plastic mulch with a single row of planting holes spaced 30.5 cm apart. Artifcially inoculated plants were transplanted in mid-November both years. The fields were fertilized with approximately 198 kg/ha of nitrogen over the growing season and irrigated as needed to prevent water stress. For the 2016–17 field experiment, 344 germplasm accessions were screened for resistance to AMP132 and were part of a study that included 565 germplasm accessions developed at UC Davis, which is hereafter identified as the ‘California’ population. The resistance phenotypes for the latter were previously reported by Pincot et al. . Collectively, 981 germplasm accessions were screened in the 2016-17 field study. These were arranged in a square lattice experiment design with four single-plant replicates per entry . The experiment design and randomizations of entries within incomplete blocks were generated with the R package agricolae . For the 2017-18 and 2018- 19 field experiments, 144 ‘host diferential panel’ individuals were screened for resistance to AMP132 . These individuals were arranged in a 12 × 12 square lattice experiment design with four single-plant replicates per entry as described above. Guardian, Wiltguard, and Earliglow S1 and 61S016P006 S2 populations were screened for resistance to AMP132 in the 2016-17 field study. Ninety-nine Guardian S1 and 98 Wiltguard S1 individuals were phenotyped and genotyped and 85 Earliglow S1 and 77 61S016P006 S2 individuals were phenotyped. Nine-month-old S1 or S2 plants started as seedlings and asexually multiplied bare-root plants of the parents were artificially inoculated with AMP132, transplanted to the field in March 2018, and visually phenotyped weekly for six to 11 weeks post-inoculation.

The 12C089P002 × PI602575 , PI552277 × 12C089P002 , and PI612569 × 12C089P002 full-sib families, 17C327P010 S1 family, and parents of these families were screened for resistance to AMP132 in greenhouse experiments at UC Davis. Two- to four-month-old seedlings of the progeny and bare-root plants of the parents were artificially inoculated with AMP132 and planted in February 2019 , June 2019 , or November 2019 into 10.2 × 10.2 × 15.2 cm plastic pots filled with 3 parts coir : 1 part perlite and phenotyped weekly for six to 12 weeks post-inoculation. Four uninoculated and four inoculated single-plant replicates of the parents were arranged in completely randomized experiment designs. The plants were irrigated with a dilute nutrient solution as needed to maintain adequate soil moisture. The 12C089P002 × PI602575 and PI552277 × 12C089P002 populations were genotyped with a 50K Axiom SNP array .We screened a host diferential panel for resistance to the MAFF727510 isolate of Fof race 2 in a growth chamber at the UC Davis Controlled Environment Facility in 2018-19. Two single-plant replicates/individual were arranged in a randomized complete block experiment design. The entire experiment was repeated twice, resulting in four clonal replications/individual. The bare-root plants for these experiments were produced in high-elevation nurseries, preserved in cold storage, artificially inoculated with the MAFF727510 isolate, transplanted into 10.2 × 10.2 × 15.2 cm plastic pots filled with a 4 parts sphagnum peat moss : 1 part perlite , and phenotyped weekly for six to 12 weeks post-inoculation. The plants were grown under a 12-hour photoperiod with a 20 °C night temperature and 28 °C day temperature and irrigated with a dilute nutrient solution as needed to maintain adequate soil moisture. Because these experiments utilized a non-California isolate of the pathogen, the experiments were quarantined and conducted in compliance with federally-mandated bio-safety regulations .

DNA was isolated from newly emerged leaves harvested from field grown plants using a previously described protocol . Leaf samples were placed into 1.5 ml tubes or coin envelopes and freeze-dried in a Benchtop Pro . Approximately 0.2 g of dried leaf tissue/sample was placed into wells of 2.0 ml 96-well deep-well plates. Tissue samples were ground using stainless steel beads in a Mini 1600 . Genomic DNA was extracted from powdered leaf samples using the E-Z 96®Plant DNA Kit according to the manufacturer’s instructions. To enhance the DNA quality and yield and reduce polysaccharide carry-through, the protocol was modifed by adding Proteinase K to the lysis bufer to a final concentration of 0.2 mg/ml and extending lysis incubation to 45 min at 65 °C. Once the lysate separated from the cellular debris, RNA was removed by adding RNase A. The mixture was incubated at room temperature for 5 min before a final spin down. To ensure high DNA yields, the sample was incubated at 65 °C for 5 min following the addition of elution bufer. DNA quantification was performed using Quantifor dye on a Synergy HTX . The individuals phenotyped in these studies were genotyped with either 50K or 850K Axiom® SNP arrays . SNP markers on the 50K Axiom array are a subset of those on the 850K Axiom array. The probe DNA sequences for SNP markers on both arrays were previously physically anchored to the ‘Camarosa’ and ‘Royal Royce’ reference genomes . The ‘Camarosa’ genome assembly has been deposited in the Genome Database for the Rosaceae and Phytozome . The ‘Royal Royce’ genome assembly has been deposited in the Genome Database for the Rosaceae and Phytozome . The assemblies for each ‘Royal Royce’ haplotype have been deposited in a Dryad repository . The physical addresses for the SNP markers are provided in our online resources . We utilized both reference genomes as needed to cross-check and compare statistical findings and search genome annotations. The results presented in this paper utilized the haplotype-resolved ‘Royal Royce’ reference genome FaRR1 unless otherwise noted. SNP genotypes were called using the Affymetrix Axiom Suite . Samples with call rates exceeding 89-93% were included in genetic analyses. The haplotypes for 71 50K Axiom array-genotyped SNPs within a 1.60 Mb haploblock on chromosome 2B were imputed and phased using BEAGLE software version 5.3 for 651 individuals phenotyped for resistanceto Fusarium wilt race 1. The individuals were classified as resistant or susceptible ,square black flower bucket wholesale where ̄y is the estimated marginal mean for resistance score calculated from replicates. We ran BEAGLE with 10 burnin iterations for imputation and 25 subsequent iterations for phasing on sliding windows of 5 Mb with a window overlap of 2 Mb.The R package lme4 was used for linear mixed model analyses of the germplasm screening experiments . LMMs for square lattice experiment designs were analyzed with entries as fixed effects and incomplete blocks, complete blocks, years, entries × years, and residuals as random effects . LMMs for randomized complete block experiment designs were analyzed in parallel to estimate the relative efficiency of the square lattice to the randomized complete block experiment designs .

We did not observe an increase in efficiency by using incomplete blocks; hence, the statistics reported throughout this paper were estimated using LMMs for randomized complete block experiment designs . Estimated marginal means for entries were estimated using the R package emmeans . Genome-wide assocation study analyses were carried out to search for the segregation of loci affecting resistance Fusarium wilt races 1 and 2 among individuals genotyped with either the 50K or 850K Axiom SNP array . GWAS analyses were applied to estimated marginal means for resistance phenotypes using physical positions of SNP markers in the ‘Camarosa’ and ‘Royal Royce’ reference genomes . SNP marker genotypes were coded 1 for AA homozygotes, 0 for heterozygotes, and -1 for aa homozygotes, where A and a are the two SNP alleles. GWAS analyses were performed using the GWAS function in the R package rrBLUP. The genomic relationship matrix was estimated from SNP marker genotypes for each population using the rrBLUP A.mat function . The genetic structure of the GWAS population was investigated using hierarchical clustering and principal components analysis of the GRM as described by Crossa et al. . To correct for population structure and genetic relatedness, a Q + K linear mixed model was used where Q is the population stratification structure matrix and K is the GRM . The first three principal components from eigenvalue decomposition of the GRM were incorporated into the Q + K model. Bonferroni-corrected significance thresholds were calculated for testing the hypothesis of the presence or absence of a significant effect. GWAS was repeated in the California population by ftting a SNP marker in LD with FW1 as a fixed effect using the rrBLUP::GWAS function .SNP markers with ≤ 5% missing data, high quality codominant genotypic clusters, progeny genotypes concordant with parent gentoypes, and non-distorted segregation ratios were utilized for genetic and quantitative trait locus mapping analyses. The linkage phases of the SNP markers were not known a priori. The arbitrarily coded SNPs in the original data were in mixed coupling and repulsion linkage phases. The linkage phases of the SNP markers were ascertained using pair-wise recombination frequency estimates, and recoded so that the 100% of the SNP markers were in coupling linkage phase. This was only necessary in the S1 populations. The recoded SNP markers were genetically mapped in S1 populations using phase-known F2 mapping functions. SNP markers were genetically mapped in full-sib populations using phase-known back cross mapping functions from the subset of SNPs that were heterozygous in the resistant parent and homozygous in the susceptible parent. Genetic maps were constructed using the R packages onemap and BatchMap and custom PERL scripts for binning co-segregating SNP markers, calculating pairwise recombination frequencies, and grouping markers using LOD threshold of 10 and maximum recombination frequency threshold of 0.05. The custom PERL scripts are available in the Dryad repository for this paper . Linkage groups were aligned and assigned to chromosomes using inter-group linkage disequilibrium statistics and percent-identity against the reference genome . Marker orders and genetic distances were estimated in parallel using the RECORD algorithm in Batchmap with a 25-marker window, window overlap of 15 markers, and ripple window of six markers . For smaller linkage groups, the window size was reduced incrementally by five to ensure at least two overlapping windows. We used the checkAlleles, calc.errorlod, and top.errorlod functions of the R package qtl and custom R scripts to identify and eliminate spurious SNP markers and successively reconstruct linkage groups as described by Phansak et al. . Genetic distances were estimated from recombination frequencies using the Kosambi mapping function .

A sub-sample of shoots and fine roots was collected for organ-dried biomass estimation and sugar and starch analysis. Harvest index was calculated after oven drying the samples.Subsamples of leaves, shoots, and roots were oven-dried at 70◦C to a constant weight. Dried tissues were ground with a tissue lyser . Thirty milligrams of the resultant powder was extracted in ethanol:water solution. Briefly, 1.5 ml was added to each sample and extracted for 10 min at 90◦C in a water bath. Then, they were centrifuged at 10,000 rpm for a minute, and the supernatant was collected for sugar determination. Total soluble sugars and individual sugars were determined in the shoot, leaf, and root ethanolic extracts and in the diluted berry must samples . Samples were filtered with PTFE membrane filters and transferred into high-performance liquid chromatography vials and subjected to reversed-phase HPLC analysis. The equipment consisted of an Agilent 1100 system coupled to a diode array detector and an Infinity Refractive Index Detector . The reversed-phase column was Luna Omega Sugar with a guard column of 5 mm. The temperature of the column compartment was maintained at 40◦C and the RID flow cell was kept at 35◦C. The mobile phase consisted of isocratic elution with acetonitrile:water at a flow rate of 1.0 ml/min with a run time of 22 min. Standard solutions of 10 mg/L of D-glucose, D-fructose, Dsucrose, and D-raffinose were injected to obtain the retention time for each compound,flower buckets wholesale and detection was conducted by RID. Sugar standards were purchased from VWR International . Sugar concentration of each sample was determined by comparison of the peak area and retention time with standard sample curves.

Starch content of the roots, shoots, and leaves was conducted using the Starch Assay Kit SA-20 in accordance with the manufacturer’s instructions. Briefly, pellets of different tissues were dissolved in 1 ml DMSO and incubated for 5 min in a water bath at 100◦C. Starch digestion commenced with the addition of 10 µl α-amylase and then incubated in boiling water for another 5 min. Then, the ddH2O was added to a total volume of 5 ml. Next, 500 µl of the above sample and 500 µl of starch assay reagent were mixed and incubated for 15 min at 60◦C. Negative controls with the starch assay reagent blank, sample blank, and glucose assay reagent blank and positive controls with starch from wheat and corn were performed. Reaction started with the incubation of 500 µl of each sample and 1 ml of glucose assay reagent at 37◦C and was stopped with the addition of 1 ml of 6 M sulfuric acid after 30 min. The reaction was followed with a Cary 100 Series UVVis Spectrophotometer and starch content was expressed as percent of starch per tissue dried weight. Weather data for the 2019 and 2020 growing seasons are shown in Table 1. Compared with the 2019 growing season, 2020 had 17 days more with temperature over 30◦C, a maximum daily temperature of 1.1◦C higher, and almost 800 mm less of precipitation, leading to an ETo of 23 mm higher. On the other hand, the lower available water for grapevine growth resulted in smaller canopy development decreasing the ETc, which explained the lower irrigation amount of 2020 compared with 2019 . Petiole mineral nutrients were not affected by irrigation amounts in the 2018–2019 growing season . Conversely, total N increased in 100% ETc, while the K content in 25% ETc vines decreased in the 2019–2020 growing season. The micronutrients were not affected by the applied water amounts in either year of the study. The plant water status decreased throughout the season . In 2019, the 100% ETc treatment had the highest SWP, while 25% ETc had the lowest SWP as expected. Conversely, there were no significant differences during the 2020 season between treatments. Likewise, we measured significant differences between the different irrigation amounts in gs and AN in both growing seasons .

We measured higher gs and AN in grapevines subjected to 100% ETc treatment from the second half of July, coinciding with the veraison, to harvest,compared with 25% ETc. The gs and AN of 50% ETc were transiently lower than those of 100% ETc, but consistently greater than those of 25% ETc. The WUE differed between irrigation amounts at harvest in 2019 and at mid-ripening in 2020 with 100% ETc grapevines showing the highest WUE . The enhancement of the photosynthetic performance in 100% ETc grapevines was accompanied by increased total chlorophyll and carotenoid content in the leaves . Calculation of the seasonal integral of SWP and gas exchange variables allowed to establish the seasonal-long trend for grapevine physiological response. Thus, SWP seasonal integrals for both seasons were affected by the interaction between irrigation amount and year. During the 2019 season, there was a significant increase of SWP with 100 and 50% ETc siSWP compared with 25% ETc siSWP . However, in the 2020 growing season, no difference in seasonal pattern was measured. On the other hand, seasonal integrals of gs , AN, and WUE were significantly different between years. The AN and WUE were significantly lower in 2020 compared with 2019 . Grapevine growth was monitored for different organs as shown in Table 3 and Supplementary Table S2. Leaf, shoot, and root fresh weights increased with increased irrigation amounts . The biomass of the leaves, roots, and shoots increased in the grapevines subjected to 100% ETc irrigation compared with 50 and 25% ETc . The applied irrigation treatments affected the harvest index . The greatest harvest index was measured in 100% ETc, while the lowest was measured in 25% ETc, respectively. Cluster number was not affected by the replacement of different fractions of ETc . An increase in the yield per grapevine was observed in both seasons with a highly significant increase in yield per grapevine in 100% ETc treatment.

Likewise, the linear increase in yield was evident from 25% ETc to 50% ETc as well, in both years. We also measured linear increases in leaf area to fruit ratio and berry size as the amount of irrigation increased from 25% ETc to 100% ETc. There was a significant increase of SS and starch content in the leaves as affected by the applied water amount . This increase in leaf SS was attributed to the increases in glucose, fructose, and raffinose content of the leaves . The total sugar and starch content of the shoots were not affected by the applied water amount . However, sucrose and raffinose in the shoots increased in 50 and 100% ETc treatments compared with 25% ETc . Root carbohydrate content and composition were not affected by irrigation treatments, with sucrose being the main soluble sugar found in root tissues . Our analysis of the different carbohydrates found in grapevine tissues indicated that starch was the main NSC in the shoots and roots, which accounted for >50% regardless of the applied water affecting their proportions . In the leaves, starch content was the less abundant NSC, but a significant effect of irrigation treatments was observed with the 100% ETc treatment reaching the highest amount. Finally, the proportions of sucrose and raffinose in the shoots decreased when water application was restricted to 25% ETc . Regarding the sugar composition of the must, fructose and glucose were the main sugars found , and their ratio ranged between 0.62 and 0.78 with no difference between treatments . In spite of the warming trends recorded for the study area within the two growing seasons covered by this study, the plant water status recorded in both growing seasons was optimal for grapevine growth as indicated by the midday SWP and the gs . Thus, seasonal integrals of SWP ranged between -0.8 and -1.1 MPa, while gs ranged between 150 and 250 mmol m−2 s −1 , in accordance to the midday SWP and gs values considered as well-watered conditions . Moreover,flower harvest buckets water status of the grapevines subjected to less applied water amount never reached values lower than -1.5 MPa for SWP and/or 50 mmol m−2 s −1 for gs , which have been reported to impair grapevine performance and berry ripening . As Keller et al. reported before, in warmer years, 100% ETc treatment may suffer from mild water deficit. Thus, under our experimental conditions, at the end of the season, especially in 2020, grapevines reached SWP values to ca. -1.2 MPa; however, they are not sufficient to impair grapevine physiology and metabolism in warm climates . Previous studies highlighted that plant water status is closely related to leaf gas exchange parameters . Thus, low values of SWP were related to decreased gs likely because plants subjected to mild to moderate water deficit close their stomata as an early response to water scarcity to diminish water loss and carbon assimilation . Accordingly, in both growing seasons, a higher SWP promoted increased stomatal conductance and, consequently, net carbon assimilation rates in grapevines subjected to 100% ETc. AN and gs peaked around veraison and then declined in all the treatments similar to several studies conducted in a warm climate before . Thus, previous studies have pointed out that limited photosynthetic performance, hence lower gs and AN values, may be triggered by passive or active signals .

Nevertheless, AN in 50% ETc treatment was not severely decreased presumably by increases in WUE, which have been related to improvements in stomatal sensitivity to water loss and vapor pressure despite the hormonal signaling from roots to shoots . Likewise, Tortosa et al. suggested that differences in WUE between Tempranillo grapevine clones were more explanatory of the variations in carbon assimilation rather than a different stomatal control. Finally, it is worth mentioning that WUE was significantly lower in the driest and hotter growing season regardless of the irrigation treatment as previously reported . Regarding intrinsic WUE , no effect due to growing conditions was observed in contrast to previous studies on vines subjected to mild water stress . The water deficits applied in this study were from moderate to severe based on SWP values; thus, it is expected that the vegetative and reproductive growth of vines will be impacted accordingly. Thus, in previous studies, higher water deficits resulted in reductions of yield and berry size . The reduction in berry mass has been associated with the inhibition of cell expansion and the diminution of inner mesocarp cell sap . The detrimental effects of 25% ETc were reported previously, suggesting that this applied water amount Vegetative growth was also impaired by water deficits applied in this study, as indicated in the decrease of leaf and root dry biomasses measured in 25 and 50% ETc treatments. Diminution of root growth under water stress has been related to the loss of cell turgor and increased penetration resistance of dried soils . In addition, a recent study suggested that the loss of leaves could decrease the supply of carbohydrates and/or growth hormones to meristematic regions, thereby inhibiting growth . In accordance with previous studies, severe water deficits led to lower shoot to root ratio because root growth is generally less affected than shoot growth in drought-stressed grapevines . Given that grapevine vegetative growth occurs soon after bud break in springtime, our results corroborated the crucial role of water availability during that period on vine development, physiological performance, and yield components reported in previous studies . Thus, irrigation of grapevines during summer could not be sufficient to fulfill water requirements when rainfall has been scarce in spring , and precipitation amounts prior to bud break result in cascading effects for the rest of the growing season that cannot be overcome with supplemental irrigation . The allocation of NSC varied between organs for which roots accounted 30%, shoots 25%, and leaves 40% of the whole plant NSCs at harvest, slightly differing from those reported for several fruit trees but similar to the works in grapevine . The NSC composition was highly dependent on the grapevine organs, with starch being the main NSC in the roots and shoots. Previous studies reported that roots accumulated the largest amounts of starch in plastids, namely amyloplasts, which is fundamental to allow rapid vegetative development during the next spring .

The task was to eliminate or minimize the flicker in the visual field three times by turning a dial that changed the intensity of a 460 nm light. Each participant performed the test while looking directly at the flickering light at 0.25, 0.5, 1, and 1.75 RE degrees, representing the MPOD level from the center to the periphery of the macula. Skin carotenoid content was measured by reflection spectroscopy . After cleaning, the tip of the right index finger was inserted into the spectrophotometer and three measurements were collected. A skin carotenoid score was calculated by the system software. Carotenoids that exist in human plasma, including β-carotene, lycopene, L, Z, and their isomers have been successfully detected in toto and quantified by this device, which has been validated to reflect fruit and vegetable consumption.Sample size was based on a study that assessed the impact of a Z supplement on MPOD in 24 healthy people. Statistical analyses were performed with JMP version 16 . Two-tailed t-tests evaluated potential between group differences at baseline. The MPOD and skin carotenoid data were analyzed with mixed-effects models using time and treatment as the main factors, with age and sex as the covariates, and participant ID as the random effect. For main effects, student t-tests determined significance within group pairs. p-Values of 0.05 or less were considered statistically significant. The mean values of the dietary intake data were compared by two-tailed t-tests, which were log-transformed when necessary,black plastic plant pots wholesale and presented as the mean ± S.E.M. or the back-transformed mean with 95% confidence intervals . Reported protocol compliance was greater than 96% for both groups, and no adverse symptoms were noted other than minor intestinal gas from one participant in the goji berry group. Table 1 presents the reported average intake of select nutrients in the habitual diet that may have affected eye health over the study period. No significant differences between groups were noted.

The composition of the goji berries is presented in Table 2. A daily goji berry serving provided 28.8 mg of Z, which was substantially higher than the 4 mg of Z present in the supplement. Although sufficient extraction of L from our goji berry samples could not be obtained, previous work by others estimated a L content of 0.15 mg in 28 g of goji berries from six different goji berry samples collected in the Ningxia province of China, the same region from which the goji berries used in this study were obtained. Baseline MPOD measures were similar between the goji berry and supplement groups . No significant interaction effects for treatment and time were observed in any REs. A significant main effect of time was found for MPOD at 0.25 RE . In a sub-analysis, intake of goji berries, but not LZ, significantly increased MPOD at 0.25 RE at day 90 compared to baseline . There was also a significant main effect of time for MPOD at 1.75 RE , with a significant increase at day 45 compared to the baseline , and again between day 90 . No significant MPOD changes were noted at any REs in the LZ group.Ninety days of 28 g of goji berry intake significantly increased the optical biomarker MPOD in healthy adults at 0.25 and 1.75 REs. These results suggest that even in a healthy population with no evidence of small drusen or early AMD, goji berry intake can improve eye health. Our results are consistent with data of improved MPOD after a similar amount and intake period of goji berry in a Chinese population at risk for intermediate AMD. Moreover, our trial is consistent with reports of protection against macular hypopigmentation and drusen development in a population of generally healthy and older individuals who were provided Z at approximately a third of the amount of Z provided in the current trial. Our findings suggest that a higher intake of Z relative to L may be useful in reducing the risk of AMD. This is consistent with increased MPOD levels after 4 months of supplementation with 20 mg Z or 26 mg Z with 8 mg L plus 190 mg of mixed omega-3 fatty acids by young healthy adults. Interestingly, we observed a significant increase in MPOD at 1.75 RE, but not at 0.5 or 1 RE, in the goji berry group.

A possible explanation for this trend is the relatively low macular pigment at 1.75 RE compared to the other REs, which may increase the potential for improved MPOD in this peripheral area of the macula. Our results are also consistent with data from 11 randomized controlled trials where supplementation with at least 10 mg of the macular carotenoids was effective at increasing MPOD. Significant correlations were observed between the overall skin carotenoid score and MPOD, which is consistent with clinical results of carotenoid supplementation. Further analysis demonstrated that L and Z, but not goji berry intake, was significantly influencing this trend. Previous work has shown an association between serum L and Z in skin and blood with macular pigment carotenoid accumulation. Data from the current trial are consistent with this observation as goji berry intake was significantly associated with the skin carotenoid score. However, in contrast to data with L and Z supplements, MPOD score was not correlated with changes in skin carotenoids with goji berry intake. The skin photometer detects overall carotenoid content, and as goji berries are also rich in β-carotene, neoxanthin, and cryptoxanthin, these carotenoids likely influenced the skin measurements, and would not reflect the selective carotenoid accumulation of L and Z in the macula. Other goji berry components such as taurine, vitamin C, zinc, and LBP may influence the results by lowering oxidant stress and improving eye health. For example, studies in animals and cell lines suggest that LBP can protect against AMD by reducing oxidative stress and cell apoptosis in retinal pigment epithelium. Taken together, under the conditions tested, it is reasonable that MPOD may not fully correlate with skin carotenoids in the goji berry group. To our knowledge, the impact of goji berry intake on MPOD in healthy middle-aged people has not been previously reported. While others have noted improved MPOD after LZ supplementation among people with low MPOD baseline levels, our findings suggest that even in populations with normal MPOD values, a significant increase can be detected after goji berry consumption at the most central part of the macula .

A meta-analysis regarding the effects of L, Z, and meso-Z supplementation noted that the MPOD at baseline was inversely associated with macular responses,black plastic plant pots bulk suggesting individuals with a relatively lower macular pigment status may receive more benefit with higher amounts of L or Z. The Age-Related Eye Disease Study 2 trial assessed the impact of dietary supplements containing 10 mg of L, 2 mg of Z, 500 mg of vitamin C, 400 IU of vitamin E, 80 or 25 mg of zinc, 2 mg of copper, and/or 350 mg of docosahexaenoic acid plus 650 mg of eicosapentaenoic acid. The results showed a significantly reduced rate of progression from intermediate- to late-stage AMD after 5 years. Secondary analyses of the study indicated protective roles of L and Z. We did not use the AREDS2 supplement for the comparison group because this formula has only been shown to be effective for those with intermediate AMD, and no clinical evidence exists for its efficacy in our study population of healthy people. In addition, we note that 80 mg of zinc in the AREDS2 supplement is twice the upper limit of recommended daily intakes for zinc. In epidemiological studies, L and Z intakes have been inversely associated with the development of AMD. In the current study, the reported dietary intake of L plus Z, not including the berries or supplement, was 3.1 and 1.9 mg/d in the goji berry and supplement groups, respectively, which is higher than the typical estimated intakes in the US of 1.6–1.86 mg/d. Three to five mg/d of L and Z have been recommended to help support normal macular function, although no recommended dietary allowance values yet exist. A few studies have explored the effects of L and Z from a whole food on MPOD. Daily consumption of one Hass avocado containing 0.5 mg of L over 6 months was associated with a significant increase in MPOD in healthy adults. In contrast, no increase in MPOD was observed after consuming one Hass avocado daily for 3 months. Daily consumption of egg yolks providing 1.38 mg L and 0.21 mg Z resulted in a significant increase in MPOD and other measures of visual acuity in older adults with signs of early stage AMD after 12 months. Another study giving older adults two egg yolks/day for 5 weeks, followed by four egg yolks/day for 5 weeks, reported increases in MPOD, but only among those with low baseline MPOD values. The addition of either spinach or corn , or the combination, for 14 months significantly increased the MPOD among the majority of healthy individuals. Our study has some limitations. Choice of a control is always a challenge in whole food studies, since masking is an issue.

A commercially available LZ supplement was used, rather than an inert capsule, since our research design was intended to compare options available to consumers and explore the role of goji berries over and above the intake of purified L and Z. The actual amount of L and Z in the supplement was not confirmed. A previous report noted that the carotenoid content of some powder-based supplements tested in 2017 did not meet label claims, while oil-based supplements did. Since L and Z are preferentially deposited at different eccentricities in the retina, the different amounts of Z in the goji berries and supplement may not be ideal. Volunteers were not screened for low MPOD as an inclusion criterion. Although the relatively modest number of participants in each group may raise some concerns, these numbers are similar to those reported by Obana et al. and are consistent with an initial probe study. Finally, although MPOD was the primary outcome measure, other ocular measurements such as contrast sensitivity and best corrected visual acuity were not assessed. Future studies on goji berry intake and eye health ideally should combine functional and anatomic measurements.Grapevine is an economically important fruit species worldwide, and has a historical connection with the development of human culture. Grapevine comprises cultivated and wild forms . More than 6000 accessions are recorded as individual varieties. Some are rare and have only a few unique vines that are important to national heritage, and are valuable as resources for cultivation and breeding. In the last few decades, the cultivated grapevine has experienced a drastic reduction in diversity due to the increased focus of the global wine industry on a few major cultivars. Moreover, the loss of natural habitat is adversely affecting the genetic diversity of the wild V. vinifera species, with some populations on the verge of extinction. Hence, immediate action to conserve indigenous grapevine germplasms is required. Vitis germplasm conservation can be achieved either in situ or Ex situ . In situ conservation refers to preserving a species in its native environment, and preserving and recovering viable populations in their natural habitat. However, anthropogenic activities and abiotic or biotic stress may lead to the extinction of the germplasm. On the other hand, ex situ conservation refers to preserving germplasm outside their native habitat. The methods include using slow growth tissue culture, cryopreservation, and seed banks; or preservation of the whole plant in a botanical garden or in a field gene bank; and via greenhouse cultivation of plant material. Using a slow growth tissue culture under in vitro conditions on minimal nutrient medium ensures minimum maintenance costs by retarding growth rates. However, this approach has several limitations, including the need for technical expertise, plant loss due to contamination of cultures, high labor costs, and the possibility of obtaining somaclonal variations. Cryopreservation in liquid nitrogen also provides an opportunity for the long-term preservation of Vitis germplasm, which can then be used as a backup for field collections for important indigenous cultivars. However, exposing cells to extremely low temperatures can result in freezing injury; hence, cells must be carefully handled and prepared before being frozen in liquid nitrogen.

These 10 alleles were examined for evidence of IHR by comparing them to the previously described non-IHR X. fastidiosa subsp. multiplex alleles and to the known X. fastidiosa subsp. fastidiosa and sandyi alleles . Of these 10, 4 alleles were found to be derived in their entirety from X. fastidiosa subsp. fastidiosa, and 3 were found to be chimeric for X. fastidiosa subsp. multiplex and fastidiosa sequences, with significant evidence of one or more recombination breakpoints. These 7 alleles encompassed 4 loci: leuA, cysG, holC, and pilU. The locus most strongly implicated in IHR wascysG, since all of the 9 recombinant-group STs were characterized at this locus by 1 of 3 cysG alleles unique to the group. The involvement of IHR in the genesis of all 3 of these alleles is illustrated by their close genetic relationship to X. fastidiosa subsp.fastidiosa and sandyi alleles . Allele 12, apart from being found in the recombinant group, is an X. fastidiosa subsp. fastidiosa allele . The other two alleles were found to be chimeric: allele 18 contains a single recombinant region at the 3= end of 342 bp, while allele 6 has two short recombinant regions, one at the 5= end of at least 23 bp and another toward the 5= end of at least 35 bp . The DNA sequence variation defining these patterns is shown in Table 2. The patterns seen in the DNA sequences of the 3 cysGalleles are consistent with the hypothesis of a single IHR that introgressed donor allele 12 into X. fastidiosa subsp. multiplex, followed by subsequent intrasubspecific recombination reintroducing X. fastidiosa subsp. multiplex sequence to create alleles 6 and 18 . There are no inconsistent sites, container size for blueberries provided the 5= recombination breakpoint in allele 18 starts after position 71. Introgression of X. fastidiosa subsp. fastidiosa sequence into X. fastidiosa subsp. multiplexwas found in alleles at 3 other loci .

In the case of pilU, 7 of the 9 recombinant STs carried either an allele identical to a known X. fastidiosa subsp. fastidiosa allele or 1 bp different from it . Allele 1 is an allele that characterizes most U.S. isolates as well as several STs found in Costa Rica, while allele 9 is unique to the recombinant group. The leuA locus has a single statistically significant recombinant allele, allele 4 . It differed by 2 bp from the X. fastidiosa subsp. fastidiosa allele 9 but by 8 bp from the most similar nonIHR X. fastidiosa subsp. multiplex allele. X. fastidiosa subsp. fastidiosa allele 9 could be the donor for its entirety , although if the recombination region started after site 10 but before position 520 , then only one site would be unexplained. That remaining site carries a base unique to this allele and is probably a novel mutation. If the recombination breakpoint was 3= of position 295 then X. fastidiosa subsp. fastidiosa allele 1 provides as good a match as allele 9 . Similarly, holC allele 7 was also 8 bp different from the most similar non-IHR X. fastidiosa subsp. multiplex allele, providing clear evidence that the 5= end was derived from X. fastidiosa subsp. fastidiosa . The pattern can be explained if X. fastidiosasubsp. fastidiosa allele 19 is the donor of the 5= region ending somewhere between positions 183 and 286, since it leaves no inconsistent bases . The loci leuA and holC each had an additional allele that were unique to the recombinant group, as was an allele at another locus, nuoL4. Although these last 3 alleles did not show statistically significant evidence of introgression , they all showed a grouping of 2 or 3 nucleotide changes that were not found in non-IHR X. fastidiosa subsp. multiplex but were present in X. fastidiosa subsp. fastidiosa. Of these 3, the strongest case for IHR is holC9, where a region of possible IHR can be seen at the 3= end of the sequence .Analysis of the recombinant group ofX. fastidiosa subsp. multiplex showed three important results. First, intersubspecific recombination was shown to have occurred in 50% of 8 loci scattered throughout the genome that were chosen independently of the data . Second, it was shown that the donor of the introgressed sequence was X. fastidiosa subsp. fastidiosa, a subspecies introduced from Central America into the United States as a single strain .

However, the introgressed sequence at two of the loci did not come from any of the X. fastidiosa subsp. fastidiosa genotypes that have been found in the United States. This result suggests that another introduction of X. fastidiosa subsp. fastidiosa must have occurred, an introduction that resulted in successful IHR, after which the donor genotype seems to have disappeared. This involvement of an unexpected X. fastidiosa subsp. fastidiosa strain supports the hypothesis that the members of the recombinant group share a single ancestral IHR event. Third, the hypothesis that IHR has facilitated a shift to new hosts is strongly supported by the example of blueberry, where 10 isolates have been typed and potentially supported by the example of blackberry .Of course, the direct causation of this link can never be proved without knowledge of the genetic changes driving this shift. It can always be argued that the link is fortuitous and that one or more point mutations in the nonrecombined X. fastidiosa subsp. multiplex genome are causal in the host shift. Arguing against this possibility are 2 additional pieces of information. First, both blueberry and blackberry are native to the United States, so if only a simple genetic change was required to infect these species, why did the native non-recombinant X. fastidiosa subsp. multiplex apparently never acquire these changes? Second, a similar but even more extensive mixing of the genomes of X. fastidiosa subspp. fastidiosa and multiplex is found in the only form of X. fastidiosa that infects another U.S. native plant, mulberry . Furthermore, in other bacterial species, it has been demonstrated that recombination can drive rapid evolution, both in the laboratory and, in the case of Helicobacter pylori, in mice . Similarly, McCarthy et al. concluded that lineages of Campylobacter jejuni in chickens versus cattle and sheep were able to shift host type, because rapid adaptation was facilitated by recombination with the resident host population.

In the study by Nunney et al. , it was shown that the recombinant genotypes formed a well-defined group , demonstrating that intersubspecific homologous recombination was not randomly distributed across the X. fastidiosa subsp. multiplex isolates. This work was based on a survey of 143X. fastidiosa subsp. multiplex isolates using just 8 loci. There were 33 isolates that showed some evidence of IHR in at least 1 locus: all but 2 showed statistically significant evidence in at least 2 loci, while the remaining 110 showed no such evidence . The generality of this discrete group of recombinant forms was supported by our analysis presented here of the sequence data from 9 more loci sequenced by Parker et al. . These loci divided isolates into 2 groups that appeared to correspond to the recombinant and non-IHR groups, respectively ,raspberry grow in pots even though Parker et al. found no evidence of IHR. Upon reanalysis, we found statistically significant IHR in 6 of the 9 loci in the clade A data but no evidence of IHR in the clade B data. Clade A included 6 isolates that we had typed in the present study, and each of these showed evidence of IHR in 4 or 5 of the additional 9 loci. Thus, in two independent samplings that together examined 17 loci, there was clear evidence of substantial genomewide IHR in the recombinant group isolates, amounting to 50% of the genes showing IHR across the MLST locis plus the pilU locus . The average was higher when based on the loci sequenced by Parker et al. ; however, this was probably biased upwards by the manner in which the loci were chosen . None of the IHR events in 6 of the 9 loci identified using the targeted introgression test, or in the case of complete introgression, a chi-square test, were detected by Parker et al. using PHI and the 9 tests implemented in RDP . This failure of the standard tests of recombination to detect IHR was previously noted by Nunney et al. , motivating the development of their introgression test. We examined the hypothesis that the recombinant group STs were derived from a single IHR event involving a X. fastidiosa subsp. multiplex recipient and an X. fastidiosa subsp. fastidiosa donor. The distribution of allelic differences among the recombinant STs was consistent with them all being derived from a single initial event, but a small number of other intersubspecific and intrasubspecific recombination events would also be needed . More importantly, the genotypes seen in the recombinant group can be accounted for entirely, or very nearly so, based on a single X. fastidiosa subsp. fastidiosa donor genotype. For example, the substantial variation in cysGcan all be accounted for by an ancestral introgression of X. fastidiosa subsp. fastidiosa allele 12 followed by subsequent intrasubspecific recombination of X. fastidiosa subsp. multiplex sequence to form the other two alleles . In contrast, variation at pilU could be accounted for by a second donor contributing the X. fastidiosa subsp. fastidiosa pilU9 allele, but it could also have arisen by a single mutation in pilU1 unique to the recombinant group. A possible single X. fastidiosa subsp. multiplex recipient genotype was also identified . This genotype is consistent with a known ST: setting cysG to allele 3 makes the recipient identical to ST45, which was sampled from the states of California, Kentucky, and Texas .

Elsewhere, we consider a slightly different hypothesis regarding the origin of the recombinant group in which the donor and recipient subspecies are reversed—i.e., that it was derived from a single IHR event, but involving an X. fastidiosa subsp. multiplex donor and an X. fastidiosa subsp. fastidiosa recipient; however, apart from the role reversal, the conclusions are unaltered . The ancestral reconstruction allows us to consider the second question posed earlier: is the donor consistent with the X. fastidiosa subsp. fastidiosa genotypes found in the United States? The answer is very clearly “no.” The original donor carried cysG12 and holC19 . These alleles are both found in isolates from Central America, but no X. fastidiosa subsp. fastidiosa isolate found in the United States comes close to matching this criterion: the most similar U.S. ST has a 12-bp mismatch. There has been extensive sampling of X. fastidiosa subsp. fastidiosa within the United States, based on 85 isolates sampled across the United States from 15 different host plants . There is very little variation within X. fastidiosa subsp. fastidiosa isolates from the United States, consistent with the hypothesis that all X. fastidiosa subsp. fastidiosa isolates currently found in the United States are derived from a single strain introduced from Central America . Based on these data, we conclude that the X. fastidiosa subsp. fastidiosa donor was introduced into the United States from Central America and recombined with a native X. fastidiosa subsp. multiplex genotype similar to ST45; however, this donor lineage of X. fastidiosa subsp. fastidiosa was ultimately unsuccessful and died out. We can never conclusively prove the absence of this genotype from North America. However, X. fastidiosa has been extensively sampled from many plant species throughout the United States, and no isolates of X. fastidiosa subsp. fastidiosa have been found that carry alleles similar to the inferred donor alleles cysG12 and holC19 ; indeed all X. fastidiosa subsp. fastidiosa isolates so far found in the United States are consistent with the introduction into the United States of just a single genotype . The transient presence of the donor genotype is consistent with a single large-scale introgression event founding the recombinant group. This raises the possibility that conjugation might have been involved; however, if this was the case, the genomic DNA was broken into pieces prior to homologous recombination, since the data show short regions of recombination. The data from the MLST loci plus pilU show 7 significant recombination events , and 3 of them included at least one recombination break point.

The values for glutamate reported for pomegranate herein are greater than values reported for grape juice , indicating increased importance for consumers regarding marketing fraud in the pomegranate juice industry because often grape juice is used as the primary adulterating agent in pomegranate juices in the USA, along with apple and pear juice. Glutamine is the amino acid of the highest concentration in human blood , which may play into the folklore regarding pomegranate juice as a “blood tonic” . Ethanol is of importance in the food and beverage industries because it is an indicator of anaerobic respiration and metabolism in post harvest fruit products. Along with other alcohols, ethanol can contribute to off flavors or even enhance the flavor of fruit if concentrations are low . The freshly expressed juice had ethanol values that were far less than the levels prohibited by countries for religious and food safety reasons, which is typically required to be less than 0.5% ethanol in the USA for the beverage to be considered non-alcoholic; religious restrictions are typically stricter.This work demonstrates the high level of phenotypic diversity of pomegranate juices that exists in approximately 5% of the USDA available pomegranate germplasm collection. This study is the first of its kind in utilizing 1H NMR coupled with conventional post harvest juice quality methodologies to assess differences among pomegranate cultivars for metabolic, physicochemical and nutritional traits. The results indicated a great complexity of juice quality and nutritional differences among the cultivars analyzed, with many fitting the profile of Wonderful, but others differing greatly from this standard. As a replacement,blueberry production alternate or substitute candidate for ‘Wonderful’ in juice markets, ‘Al Sirin Nar,’ ‘Blaze,’ ‘Desertnyi,’ ‘Parfianka,’ ‘Phoenicia,’ ‘Purple Heart,’ and ‘Sakerdze,’ all meet a host of juice quality parameters and mostly fit the nutrition composition of ‘Wonderful.’

These varieties should be considered for further investigation via cultivar trials to determine phenotypical traits important to growers and taste panels to determine preferences of consumers. There were striking differences between the commercial juice and fresh-squeezed juices as well as significant differences between juice extraction methods for many parameters, including amino acid content, phenolic content and antioxidant activity. Potassium concentration varied greatly among cultivars, which can affect the flavor and nutritional composition of these fruits and their juices. This work also presents further evidence that pomegranate is not only a potentially healthy fruit in terms of phenolics and antioxidant activity, but also for nutrition as it relates to amino acids and mineral nutrition . It is important to note that these juice quality traits and nutritional factors can be significantly different among cultivars. Whether the cultivars with unique quality profiles appeal to consumers will need to be investigated in future research. This study is the first of its kind comparing fresh-pressed juice quality of the industry standard, Wonderful, with 13 other NCGR pomegranate cultivars using 1H NMR coupled with other physicochemical analytical techniques. Pomegranate is a deciduous tree crop that has been domesticated for thousands of years for its fruit, flowers, bark, and leaves , all of which have been believed to possess medicinal properties . Despite its long history of cultivation, limited horticultural information is available for growers, breeders, and the food and beverage industries about when fruit of a given cultivar is ready for harvest, processing and consumption . In the United States, Wonderful, the industry standard, is a tart, acidic, moderately hard-seeded fruit that has been reported to have astringent and bitter juice compared to other cultivars previously analyzed from the collection at the United States Department of Agriculture – Agricultural Research Service National Clonal Germplasm Repository , Davis, CA .

Despite these negative fruit quality traits, pomegranate cultivation in the United States remains predominantly a monoculture of ‘Wonderful.’ It is believed that cultivars in the national germplasm with desirable traits, such as soft seededness and low acidity may be candidates for commercial production. Studies have demonstrated a large variation in mature fruit size within commercial orchards of ‘Wonderful,’ which poses a problem for fresh market growers and packers. Wetzstein et al. reported a greater than five-fold range in mature fruit volume and weight in commercial ‘Wonderful’ pomegranate groves. Factors that influence fruit size and yield include aril number , cultivar , cultural practices , and plant maturity . Finding cultivars with better uniformity than Wonderful would be beneficial to the industry In addition to variable fruit size, dates of fruit maturity can play a major role in fruit quality. Late season harvests run the risk of fall rains, which have been associated with greater numbers of split fruit . Typical commercial harvest windows for ‘Wonderful’ range from late September to early November, but fruit in the Central Valley of California, USA, where the most pomegranate cultivation occurs, are typically ready to harvest starting in late October. Usually by November, effects of weather, especially rains, and pests will begin to damage the fruit. Therefore, harvest date can determine whether a cultivar is a good candidate for commercial production. In addition to the fresh fruit market, pomegranates are also utilized for juice. The beverage and wine industries utilize different fruit juices that have sufficient quantities of organic acids, carbohydrates , and phenolic compounds. Concentrations of total soluble solids , often expressed in ºBrix, for commercial pomegranates range from 12% to 16% at maturity. It is recommended that ‘Wonderful’ have at least 15% TSS at harvest , but above 17% is preferable . Hasnaoui et al. reported that citric acid is the determinant of sour flavor in pomegranate juice, despite sugar concentration. Sweet pomegranates typically have been reported to have citric acid concentrations less than 0.50% . Standards for fruit maturity of sweet cultivars are being investigated because growers often pick early-season cultivars too early in order to increase profits .

There are no known imposed regulations on growers in any country, meaning they can harvest early before fruit maturity without short-term consequence. The effect of picking early on consumer perception and acceptance of pomegranate fresh fruit has been shown to be associated with astringency and a low flavor preference score . Standards have been proposed for titratable acidity and total soluble solids for ‘Wonderful’ pomegranate . Generally, citric acid is the most abundant organic acid in pomegranate juice, so TA is generally expressed in citric acid equivalents. ‘Wonderful’ pomegranate fruit is considered mature when juice is lower than 1.85% TA , so fruit are picked when fruit measure below that threshold. Maturity index is a standardized measure of maturity in many fruit crops. For pomegranate, a commonly used MI is the ratio of °Brix to TA, also known as the sugar to acid ratio. This ratio is often used to determine fruit maturity, but it has been found to not be usable for sweet cultivars. Instead, fresh aril weight is used at the indicator of fruit maturity and consumer acceptance in the sweet cultivars . The optimum MI for ‘Wonderful’ has been calculated to be greater than 8.1, at which point the fruit is ready for harvest. Other cultivars may have significantly different quantities of organic sugars and acids, so MI is logically different for different types of pomegranates . Fruit quality is not only related to sugar content, titratable acidity and spoilage, but also to phenolic compounds that contribute to the fruit’s flavors, antioxidant activity, and color . Cultivar is more influential in determining fruit juice composition than site of cultivation, year of harvest, or length of storage ,blueberry in container so it is important to study differences in traits among cultivars to identify superior cultivars in germplasm resources and make them available to growers and consumers. Determining levels of phenolics and the antioxidant activity of a cultivar’s juice is important to the beverage industry and consumers, because advertisements promote high antioxidant activity as the main selling point of juice products. If any cultivar were to demonstrate similar antioxidant activity to Wonderful, it would possibly be competitive in the pomegranate market were it to meet other consumer preferences. Having lower antioxidant activity than ‘Wonderful’ could make for an undesirable candidate for commercial production, although the public is unlikely to be able to detect differences in antioxidant activities. The objectives of this research were: 1) to evaluate fruit and juice quality traits of NCGR germplasm by comparing commercial quality parameters to the industry standard, Wonderful; and 2) to determine potential harvest windows of ten preselected pomegranate cultivars, based on seasonal trends of potential maturity indices with harvest dates. Fruit were harvested from the USDA-ARS National Clonal Germplasm Repository for Tree Fruit and Nut Crops and Grapes in Davis, CA, USA for two seasons. The trees were all over nine-years-old and in full maturity. The pomegranate cultivars analyzed included: Ambrosia, Desertnyi, Eversweet, Golden Globe, Green Globe, Haku Botan, Loffani, Parfianka, Phoenicia, and Wonderful . The cultivars in this study that have been described as soft-seeded included Desertnyi, Eversweet and Parfianka. Low acid cultivars included Ambrosia, Desertnyi, Eversweet, Golden Globe, Green Globe, and Loffani. Wonderful fresh fruit was included as a control and as the standard to compare the other cultivars in this study. All cultivars are of American origin except for Haku Botan and Desertnyi and Parfianka . Up to twelve fruit of each cultivar were hand-harvested in mid-September, midOctober, and mid-November in 2014. This was repeated in 2015.

Fruit were ground shipped, and then stored at 6 °C and 98% relative humidity for 3-4 weeks until processing. Fresh market quality fruit, as defined by being well-filled, mature, and unblemished, were chosen for juice analysis from each of the 10 cultivars. Three cultivars, Golden Globe, Green Globe and Parfianka, had fruit damage in November, so less fruit were available for these cultivars during November harvest dates. ‘Golden Globe’ and ‘Parfianka’ had no fresh market quality fruit available in November 2015 and ‘Green Globe’ had no fresh market fruit available for 2014 and 2015. At this last season harvest, the trees of these cultivars had fruit that were either cracked or infested with insect pests, especially leaf footed bug.Up to 12 fruit per cultivar were weighed using a tared digital scale. The equatorial diameter and stem- to blossom-end length of each fruit and calyx length and diameter were measured with a digital caliper. After weighing and measuring, fruit were opened by scoring the peels of the fruit longitudinally with a scalpel. Arils were then manually extracted from a subsample of five fruit. Weight of 100 arils and total aril weight was determined with a tared digital scale. Only intact, non-damaged arils were weighed for the weight of 100 arils to reduce error. Edible fruit fraction was determined by dividing weight of all arils by the total weight of fruit and converting the result to percent. For juice processing, fruits were halved and 100 undamaged arils were manually removed and placed in a polyethylene bag. These arils were pressed manually with approximately 480 Newtons of force to express the juice directly into a 15 mL test tube. Raw juice samples were transferred to a centrifuge tube via pipette and were centrifuged at 1000 g for 5 min using a Becton Dickinson DYNAC Centrifuge . Aliquots of the supernatants were used for all chemical analyses. 5.2.3 °Brix Degrees Brix, also known as total soluble solids, were quantified with a Vee Gee Scientific PDX-1 Digital Refractometer , utilizing 0.5 mL sample of expressed, centrifuged juice. Individual juice samples, each one representing a single whole fruit, were transferred to the refractometer sample reservoir with a hand pipettor. The sample reservoir was cleaned by spraying with deionized water with a wash bottle and wiped dry with Kimwipes before each subsequent sample. Results were reported in °Brix and represented the relative percent sugar content of the centrifuged pomegranate juices. One measurement was taken for each juice sample. Juice TA was measured with a Hanna HI 84532 fruit juice TA mini-titrator . Samples were prepared by mixing individual centrifuged juice aliquots with 45 mL of deionized water. Each sample represented the juice of one whole fruit and 3 to 5 samples were analyzed for TA per cultivar. Because the predominant organic acid in most pomegranates is citric acid, results are expressed in citric acid equivalents, which represent percentage citric acid in juice solution.

Some of these early cultivars include Foothill Early, Granada, and Early Wonderful. These cultivars reach maturity long before fall rains, which can be devastating to pomegranate crop yields due to fruit splitting . However, the early cultivars listed have been described as inferior compared to the fruit and juice quality of Wonderful, specifically having lower internal color quality . However, it is important to note that different cultures prefer differing flavor profiles for pomegranates. Pomegranate is utilized for many products, ranging from fresh fruit to various types of value-added products. Value added products can be from the seeds, which contain fleshy, juice-containing arils, which are the outer integument of the seed, or from the fruit peel. Maestre et al. reported that uses for pomegranate fruit include juice, jams, preserves, jellies, refrigerated arils, frozen arils, liquors, syrups and soft drinks. These various uses for pomegranate can be dependent on the cultivar that is being utilized. For example, jellies produced with ‘Borde’ experience fewer losses than ‘Mollar’ pomegranate when stored at higher temperatures. Yoshimura et al. reported that pomegranate is a successful skin whitening agent in mammals, which could be utilized as a plant-source material in the cosmetic or pharmaceutical industries. Per Stover and Mercure , as a fresh fruit, consumer demand for pomegranate may increase with the introduction of cultivars with soft-seeded arils and uniquely colored and sweeter arils. Day and Wilkins also believe that both commercial growers and consumers may express interest in cultivars other than Wonderful if they were to have “unusual” or “unique” traits. As a whole fresh market fruit, pomegranates should be medium to large at harvest and their exterior color should be pink or red , but it should be noted that market preferences have changed in the past, as with Malus and Prunus crop species. In the United States,big plastic pots the most important product produced from pomegranates is juice . The beverage industry has a market value of $187.4 billion, with total fruit juice sales equal to $50 billion .

Previous market research found that pomegranate juice was ranked first in the super premium juice category in grocery store sales and that PomWonderfulTM juice was the leader in pomegranate juice sales, with $36.5 million in sales during the time of the study . Market research also suggested that for juice blends, pomegranate-blueberry blends had the best sales. In addition to consumer acceptance of the fruit, to be a successful commercial cultivar, a cultivar must be easily propagated in the nursery and readily established in a commercial orchard; otherwise, it would be difficult to implement commercial production for that genotype. Compared to all other methods of propagation, utilizing dormant hardwood cuttings is the most inexpensive and convenient method to propagate pomegranate. As a result, it has become the standard for the industry for the production of clonal bare root or container-propagated trees . Perhaps the most important reason pomegranate trees are propagated via stem cuttings is that the seeds of pomegranate are the product of sexual reproduction and if propagated by seed, the progeny are not true to type . As a result, seeds are not utilized in the nursery industry for production of commercial pomegranate trees. Historically, pomegranate was propagated commercially by dormant hardwood cuttings in California long before the first scientific reports on pomegranate were published by the University of California . Although many studies have been conducted on propagation of pomegranate via hardwood cuttings , none of these studies is known to have included any of the cultivars from the USDA-ARS NCGR. In addition, there are no data in the literature regarding dormant cutting propagation of the most important commercial cultivar in the United States, Wonderful. Another omission from the literature is the lack of information on vegetative growth parameters of the cultivars in the collection. These parameters may elucidate important horticultural traits, such as plant vigor, branching habit, and the proportion of buds that produce vegetative shoots, including the proportion of buds below the soil-line that produce both vegetative shoots and roots. Success rate and vegetative growth parameters are important characteristics for professionals in the nursery industry and commercial growers.

Research on pomegranate propagation typically utilizes hardwood cuttings with stem lengths of 20 cm or more . Whereas it may be optimal to use 20 cm of stem length for hardwood cuttings, the most limiting factor to crop expansion of pomegranate in California is the lack of nursery stock . Alikhani et al. reported that cuttings with three buds or more givethe best results for clonal hardwood propagation; Heidari et al. found evidence that single node cuttings worked better than those having two or four buds. This finding was ascribed to the endogenous hormonal balance in the propagule. Reports on the use of the auxin indole-butyric acid to increase rooting are contradictory. Polat and Caliskan reported that 1 g×L -1 of IBA was sufficient to root pomegranate cuttings, but stated that this concentration was not optimal. Saroj et al. reported that 2.5 g×L -1 IBA was an optimum rate of auxin for high rooting success in pomegranate. However, much higher doses of IBA have been demonstrated to increase pomegranate propagation success, with a treatment of 12 g×L -1 resulting in a lower rooting success rate . To be considered for commercial pomegranate production, a pomegranate cultivar would need to produce high yields and be as precocious as Wonderful. Wonderful typically starts producing an economic crop in year three after planting , so any variety that produces fruit in year three or earlier could possibly be a competitive cultivar relative to the industry standard. The cultivar would also need and acceptable establishment rate, i.e. to quickly reach a tree size that partially fills the 4 m x 5.8 m spacing typical of pomegranate groves within the same time or earlier than Wonderful, excluding cultivars with dwarf and semi-dwarf traits that could be farmed in high density plantings. Another trait of benefit to a commercial cultivar is having an earlier harvest date than Wonderful, which is typically harvested for the fresh market in late September, October, or early November, depending on climate and growing conditions. For juice production, ‘Wonderful’ trees are stripped at the end of the commercial fresh fruit production season, which can be as late as November. The cultivar must also maintain good fruit quality over this period to be competitive with Wonderful. Having an earlier harvest date is ideal because it will increase the chances of avoiding fall rains, which are known to cause devastating losses due to fruit splitting.

Orchard establishment rates for pomegranate cultivars under drip irrigation are unknown. Day et al. found that ‘Wonderful’ trees will produce a commercial crop by the third year in the field under furrow irrigation in the San Joaquin Valley in Central California, but plant establishment data were not collected. No data are available for tree height, canopy width within a row or across the row or trunk diameter, the traits which were measured by Webster et al. to determine establishment rates in apple cultivars. These traits are important in all tree crops. Comparisons of tree establishment rates across different climates are also not found in the literature. For a commercial fruit tree grove to be sustainable and profitable, the trees need to be precocious, i.e., to produce as many flowers and fruit of marketable quality, as early as possible . Pomegranate is monecious and produces two flower types, functionally “male” and functionally “female.” Male flowers only produce pollen and have an underdeveloped gynoecium, whereas the female flowers are perfect and are able to produce fruit . To ensure that precocity is not a false measure of the ability of a tree to set fruit, the number of male and female flowers during peak bloom must be counted on each tree . Pomegranate is a crop that can survive in relatively harsh conditions and it has been classified as a drought- and heat-tolerant crop . Glozer and Ferguson reported that pomegranate trees tolerate temperatures as low as -11° C. The geographical suitability of cultivars for commercial production at a given site can also be assessed by quantifying physiological parameters influencing tree health, growth and productivity. These parameters include photo inhibition, stomatal conductance, transpiration and photosynthetic rate. To determine satisfactory geographic suitability and success,growing berries in containers a cultivar would have to perform physiologically at an equal or greater level than Wonderful. Hepaksoy et al. found evidence that leaf transpiration and water-use efficiency were correlated with fruit splitting in pomegranate. Additionally, being able to forecast establishment rates and precocity of the cultivars is crucial to assess whether a cultivar is a candidate as a commercial cultivar and it allows growers to anticipate establishment of their trees. In addition, information on tree size and growth habit is important to evaluate a cultivar’s suitability for trellising or high density planting.

The pomegranate fruit is often classified as a berry , or it is considered berry-like , having a “leathery” exocarp that ranges in color from light yellow to black , although in the market, pomegranate fruit are typically a bright red color. Peel texture can range from soft to tough. Mature fruit are spherical with a calyx at the blossom end , which closely resembles a crown. After fertilization, sepal color typically changes from orangered to green, but can vary among cultivars. As the fruitlet develops, the fruit’s color typically changes from green to the color of that genotype at maturity . Pomegranate seeds are arranged in locules that are separated by white to yellowish septa, inedible mesocarp tissue , which are not evenly distributed in the fruit . The septa are inedible because they are comprised of insoluble fiber . Locules at the stem end are generally more numerous than those at the calyx end . The epidermis of each seed is fleshy and is botanically referred to as a sarcotesta or aril. The flavor and color of the sarcotesta is cultivar-dependent, ranging from sour to sweet and white to deep purple, respectively. The hardness of the seeds, amount of juice contained in the arils, and aril size are also cultivar dependent . A large pomegranate fruit can contain up to 1200 to 1300 seeds . Pomegranate is a non-climacteric fruit, meaning that it matures and does not ripen . Differences in seed number may affect a cultivar’s ability to be successful in the prepackaged aril market, which has developed considerably over the last five years. Studies have demonstrated a large variation in mature fruit size within commercial orchards of ‘Wonderful,’ which poses a problem for fresh market growers and packers. Wetzstein et al. reported a greater than five-fold range in mature fruit volume and mass in commercial ‘Wonderful’ pomegranate groves. At maturity, pomegranate fruit are typically 3.5 to 6.5 cm in diameter with a mass of 30 g to several hundred grams , although commercially-valuable pomegranates typically weigh more than 400 g and the largest-sized ‘Wonderful’ fruit from mature trees can have a diameter of over 100 mm . Factors that influence fruit size and yield include aril number , cultivar , cultural practices , and tree age . Cultivars that show greater uniformity in fruit size would be beneficial to the industry due to the fresh market sizing problems reported for Wonderful by Wetzstein et al. . Typical commercial harvest windows for ‘Wonderful’ range from late September to early November, but fruit in the San Joaquin Valley of California, USA, where the most Punica cultivation occurs, are typically ready to harvest starting in late October. Usually by November, the effects of weather and pests will begin to take a toll on mature fruit. Harvest date can determine whether a cultivar is a candidate as a commercial cultivar. Cultivars with an earlier fruit maturity date have a better chance of competing with Wonderful in the market. Later cultivars run the risk of fall rains, which have been associated with greater numbers of split fruit and a loss in fresh market sales . The beverage and wine industries utilize fruit juices that have sufficient quantities of organic acids, carbohydrates , and phenolic compounds. For commercial pomegranate fruit, concentrations of total soluble solids range from 12% to 16% at maturity, but ‘Wonderful’ should have at least 15% TSS at harvest . Hasnaoui et al. reported that citric acid is the determinant of tart flavor in pomegranate juice, and this is said to be independent of the sugar concentration.

In retrospective observational studies on hot topics , thousands of independent analytic teams may approach a similar question—all with different plans. This field-wise multiple hypothesis testing has been shown experimentally to generate both positive and negative statistically significant associations, simply by analytic choices. Even when data sets are standardized, multiple analytic approaches may yield a range of answers to a single question. Finally, randomized controlled trials, the gold standard of causal inference, have historically been immune to questions of multiple hypothesis testing, although this is increasingly being called into question with the emergence of redundant, duplicative, and large trial portfolios. In this commentary, we explore the role of multiplicity in biomedical research—a growing challenge to the interpretation of individual study results.Consider the case of nutritional headlines that dominate the front pages of prominent news outlets such as The New York Times’ health section. One week, researchers may suggest that blueberries or dark chocolate have been shown to reduce your risk of cancer, but the next week, these same exposures may be found to increase your risk. What explains this phenomenon? To begin, for popular topics, it is likely that thousands of individual analyses of a data set will be performed over a relatively short period of time, each controlling for some co-variates—those that researchers believe are plausibly related to an outcome—in an effort to uncover a meaningful correlation. Each of these models will create a new relationship between the investigated variables,planting blueberries in containers as Patel et al. demonstrated by simulating the research community of nutritional epidemiology.The authors used the National Health and Nutrition Examination Survey and probed a series of nutritional exposures, asking if they increased or decreased overall mortality.

For each exposure, the researchers used baseline variables and the 13 most common co-variates adjusted for in the sampled literature [e.g. ‘, hypertension, diabetes, cholesterol, alcohol consumption, education, income, family history of heart disease, heart disease, any cancer, physical activity and race/ethnicity’].Then, the entire research community was simulated. Over 8000 different models were generated for each exposure-mortality association by combining all conceivable combinations of the 13 modifiable demographic factors. They found that the majority of studies showed no significant association. But, what was noteworthy is that for 31% of the variables, there were both statistically significant positive and negative outcomesforthe same hypothesis, indicating that the hazard ratio could be HR>1 or HR ≤1 with a significant p-value depending on the level of co-variant adjustment.Researchers called this the vibration of effects. Schoenfeld and Ioannidis extended this result in an analysis measuring 50 common ingredients randomly selected from a cookbookThen, the researchers conducted a literature search on articles that measured each ingredient’s link to cancer. Most of the ingredients had articles measuring their relation to cancer risk. Despite many weak and non-significant relationships, most ingredients had studies with outcomes contrary to each other, showing either an increased or decreased risk of developing cancer.Zaorsky and colleagues applied the vibration of effect approach to practical questions in cancer medicine. They found that by varying other analytic choices—leftt truncation adjustment, propensity score matching, landmark analysis, and different combinations of co-variates—they were able to generate any desired result.These are all instances of a common theme when dealing with multiplicity:studies measuring the same research question yielding opposite findings.Work by Silberzahn et al. demonstrated a similar situation of multiplicity when they categorized the skin tone of different soccer players and included it in a data set with reports of penalties to 29 research teams.The following question was posed to the teams: Were soccer referees more likely to issue a dark-skinned player a red card, signalling a penalty, than they were a light-skinned player? Twenty of the teams reported significant evidence of bias, whereas nine teams discovered a non-significant relationship, with one team finding a trend in the opposite direction .These different analytical strategies provide researchers with a great deal of latitude, allowing for the potential of a myriad of distinct outcomes.

However, the issue intensifies when one considers that significant findings are more likely to be published,resulting in a dichotomized literature devoid of a middle ground of null results.Randomized controlled trials have historically been thought to be immune to multiplicity as rarely are hundreds or thousands of studies run on a single clinical question, but this fact may be shifting. There are now four critical considerations to examine regarding the relationship between multiplicity and oncology: The United States Food and Drug Administration will approve drugs based on a single positive trial, even if the primary outcome is a surrogate endpoint, and even if other trials are negative; Drug approvals often generate enormous financial windfalls; Pharmaceutical companies tend to conduct large, duplicative trials with little rationale; and The probability value is arbitrary. First, consider neratinib, the only drug ever approved in the adjuvant setting prior to the metastatic. Approval was based on a single placebo-controlled Phase III trial measuring invasive disease-free survival as a primary composite endpoint. The magnitude of benefit was small, with 5.1% and 1.3% improvements in 5-year iDFS rates in patients with hormone receptor-positive breast cancer who began therapy with trastuzumab less than one 1-year ago or more than 1-year ago, respectively.Additionally, there are occasions when a medicine, such as adjuvant sunitinib in renal cancer, is approved despite the existence of a single negative trial and a single positive trial, thus ignoring the study portfolio.The second and third points may be coupled; approvals of cancer drugs are anticipated to yield billion-dollar profits,which encourages the conduction of duplicative studies in many tumour types, despite weak evidence. Consider the genesis of the EVOLVE-1 study, which compared everolimus with placebo in patients with advanced hepatocellular carcinoma following sorafenib failure.The maximum tolerated dose and the disease control rate were tested in early Phase I and Phase I/II studies, respectively, which laid a relatively weak foundation for expediting the EVOLVE-1 trial, rather than conducting a more conservative Phase II trial.Despite the negative outcome of the trial, one reason for taking such an enormous financial risk is because, despite the high upfrontcosts of conducting these large trials, a far larger financial incentive remains, namely drug approval if the trial is successful. However, the case of everolimus is just one example in the broader landscape. Consider that approximately 700 clinical studies were conducted in a single year for pembrolizumab, and that when more and more tumour types are evaluated, the risk/benefit profile of the drug deteriorates, as was shown during the development of sunitinib monotherapy.

Even with negative trials and worsening aggregate risk/benefit profiles, a drug approval’s billiondollar return greatly outweighs the initial expense of conducting million-dollar studies. Fourth, consider the most widely used statistical instrument, the p-value. If researchers run 100 trials to determine the effect of an inert drug on survival and assume a one-tail p-value of p<.05, a distribution of five trials on average will have a false-positive result. This is precisely the definition of the p-value—the probability of seeing this result or a more extreme result if the null hypothesis is assumed. This value is an arbitrary line in the sand, although arguably a necessary one that is admittedly susceptible for misinterpretation. These concepts are illustrated in Figure 1. The left side represents a single, large pan-tumour RCT for a novel cancertherapy that was negative. In an analysis of prespecified subgroups, there were some tumours with positive results. Is it likely that a positive subgroup finding may result in FDA approval for a particular indication? The answer to that question is no. The FDA would perform adjustments for multiplicity, and in the absence of that, the findings are, at most, hypothesis generating. Now consider that instead of conducting a single RCT, several, separate RCTs were conducted in numerous indications, approximating the mentioned subgroups . Some of these studies may be positive in the same subgroups, perhaps even by chance alone, but the overall portfolio may be the same. The difference is that now these findings will result in drug approval. The reality is that, although each of these studies in orange were performed independently, they represent a trial portfolio. Both situations are philosophically equivalent as they test a single hypothesis , and on the left, the bias is clear, but on the right, positive trials appear distinct, and the portfolio is never assessed in aggregate. Because the trial portfolio is not considered in the present oncologic regulatory environment,container growing raspberries multiplicity must be accounted for. One example that illustrates how statisticians and cancer doctors may view a question different is also captured in Figure 1. Some statistical experts have suggested meta-analyses be used for the figure on the Right , rather than multiplicity testing.However, these approaches fall short of answering the pertinent clinical question because the drug is considered in aggregate in multiple tumour types repeatedly, rather than identifying whether a drug works in one tumour or the other.A meta-analysis or pooled estimate focuses on determining whether a drug is effective in all tumour types, rather than the cancer doctor’s question of which tumour the treatment is effective in–a distinct difference. Because this technique does not exclude the possibility of a single positive trial leading to drug approval, multiplicity adjustment is needed to sate the doctor’s and patient’s question, and not a pooled estimate. This scenario also illustrates the importance of content specific experts guiding the framing of the statistical question. Combining all the key points above, businesses are now incentivized to test drugs with marginal benefits in as many indications possible. Consider that when a pharmaceutical firm develops a drug, all translational research costs are expended, leaving just the expense of additional trials. When companies consider this sunk cost, which requires no further investment in research and development but just the expense of the additional trial at the end, it incentivizes the company to test it in every single tumour type as many times as possible.

When combined with the low bar for drug approval, the considerable post-approval revenue, and a generation’s threshold of significance, pharmaceutical companies stand to profit enormously. Because these therapies are likely more effective than an inert substance, both true and false positives are obtained, which when averaged, results in a highly profitable approach. We see this with immune checkpoint inhibitor trials. There are now thousands of studies of largely similar molecules with massive duplication in the same or similar cancer settings,often yielding conflicting results.Hyperkalaemia is a common electrolyte abnormality which occurs most frequently in patients with decreased kidney function, with the highest prevalence observed in patients with end-stage renal disease . Severe hyperkalaemia is a medical emergency, as high serum potassium levels or its abrupt excursions may be a cause of sudden cardiac death. Besides a decrease in potassium excretion by the kidneys or ESRD and often made worse by medications such as inhibitors of the renin-angiotensin-aldosterone system, hyperkalaemia may also be exacerbated by an abnormal redistribution between the intracellular and extracellular space and by increased dietary potassium intake. In the early stages of CKD, even very high potassium intake is not sufficient to cause hyperkalaemia and external potassium balance is generally neutral, unless therapies reducing net intracellular shift or renal excretion capacity are administered. This is an important consideration since high potassium diets are useful in patients with CKD because they have been associated with favourable cardiovascular and renal outcomes. However, in advanced stages of CKD and in ESRD a positive external potassium balance, namely a dietary input that surpasses output, has a crucial role in engendering hyperkalaemia, and its prevention requires a balanced management of dietary potassium load. The present paper aims to review dietary potassium handling and gives information about practical approach to limit potassium load in CKD patients at risk of hyperkalaemia. Whereas the US Food and Nutrition Board of the Institute of Medicine has set an adequate intake for potassium relatively high in healthy adults, i.e. 4.7 g per day, the World Health Organization recommends a dietary potassium intake of 3.9 g per day or at least 90 mmol/day , to reduce blood pressure and the risk of cardiovascular damage, stroke and coronary heart disease. In patients with non-dialysis dependent CKD stages 1–5, the National Kidney Foundation suggests an unrestricted potassium intake unless the serum potassium level is elevated. In hemodialysis patients, potassium intake should be up to 2.7–3.1 g/day and in peritoneal dialysis patients close to 3–4 g/day; in both cases, adjustments based on serum potassium levels are crucial.

Similarly, bile acid molecules such as muricholic acid and taurocholic acid were more abundant in IHH-exposed versus control animals. Bile acids are crucial for not only facilitating transport of dietary fats and cholesterol in the host but also regulating host energy expenditure, glucose homeostasis and anti-inflammatory immune responses . Many metabolic and cardiovascular conditions have been associated with aberrant bile acid profiles, suggesting that prolonged perturbations in these key molecules could contribute to downstream adverse cardiovascular consequences of OSA as well. In summary, our work provides reproducible candidate biomarkers of IHH-exposure in animal models and will be most applicable to designing diagnostic and treatment modalities. Furthermore, by identifying consistent alterations across different model systems, we outline a general pipeline to select for biomarkers and therapeutic targets applicable to other intervention studies as well. We have made these information rich datasets publicly available to promote collaborative progress in this area of research.Intermittent hypoxia and hypercapnia was maintained in a computer-controlled atmosphere chamber system as previously described . IHH exposure was introduced to the mice in short periods of synchronized reduction of O2 and increasing of CO2 separated by alternating periods of normoxia and normocapnia with 1– 2 min ramp intervals for 10 hours per day during the light cycle. This treatment protocol mimics the severe clinical condition observed in obstructive sleep apnea patients. Mice on the same HFD but in room air were used as controls. Fecal samples were collected at baseline and twice each week for 6 weeks or 10 weeks .We performed 16S sequencing on fecal samples from Ldlr-/- and ApoE-/- mice for all the time points. DNA extraction and 16S rRNA amplicon sequencing were done using Earth Microbiome Project standard protocols .

In brief, DNA was extracted using the MO BIO PowerSoil DNA extraction kit . Amplicon PCR was performed on the V4 region of the 16S rRNA gene using the primer pair 515f to 806r with Golay error-correcting barcodes on the reverse primer. Amplicons were barcoded and pooled in equal concentrations for sequencing. The amplicon pool was purified with the MO BIO UltraClean PCR cleanup kit and sequenced on the Illumina HiSeq 2500 sequencing platform. Sequence data were demultiplexed and minimally quality filtered using the QIIME 1.9.1 script split_libraries_fastq.py,nursery pots with a Phred quality threshold of 3 and default parameters to generate perstudy FASTA sequence files. The raw sequence data were processed using the Deblur workflow with default parameters in Qiita . This generated a sub-operational taxonomic unit abundance per sample . Taxonomies for sOTUs were assigned using the sklearn-based taxonomy classifier trained on the Greengenes 13_8 99% OTUs in QIIME 2. The sOTU table was rarefied to a depth of 2,000 sequences/sample to control for sequencing effort. A phylogeny was inferred using SATé-enabled phylogenetic placement, which was used to insert 16S Deblur sOTUs into Greengenes 13_8 at a 99% phylogeny.We acquired LC-MS/MS data on fecal samples from Ldlr-/- and ApoE-/- mice using identical protocol. Details of data acquisition parameters are specified in . Briefly, fecal pellets were extracted in 500 µl of 50:50 methanol-H2O solvent, followed by centrifugation to separate insoluble material. The extracts were dried completely by centrifugal evaporation and resuspended in 150 µl of methanol-H2O . After resuspension, the samples were analysed on a Vanquish ultrahigh-performance liquid chromatography system coupled to a Q Exactive orbital ion trap . A C18 core shell column with a flow rate of 0.5 ml/min was used for chromatographic separation . The raw data sets were converted to m/z extensible markup language in centroid mode using MSConvert . All mzXML files were cropped with an m/z range of 75.00 to 1,000.00 Da. Feature extraction was performed in MZmine2  with a signal intensity threshold of 2.0e5 and minimum peak width of 0.3-s. The maximum allowed mass and retention time tolerances were 10 ppm and 10 s, respectively.

Local minimum search algorithm with a minimum relative peak height of 1% was used for chromatographic deconvolution; maximum peak width was set to 1 min. The detected peaks were aligned across all samples using the above-mentioned retention time and mass tolerances producing the final feature table used in these analyses. We performed molecular networking in GNPS to putatively identify molecular features using MS/MS-based spectral library matches. We analyzed them using the same LC-MS/MS method described above to compare and verify the exact masses, fragmentation patterns, and retention times to ensure level 1 annotations, as defined by the 2007 metabolomics standards initiative .We calculated the sharedness of microbial features as follows. To quality-control the 16S sequences obtained per animal model, we retained only reads that were prevalent within each model i.e. above a sum relative abundance threshold of 10E-06 and present in at least 1% of the samples, thus avoiding sequencing noise. The number of such reads in Ldlr-/- and ApoE-/-animals was 635 and 582, respectively. Out of these, 248 sequences were shared between the two models. Therefore, the percentage of microbiome features shared between the animal models was 39% of unique microbial features found in Ldlr-/- models. For metabolomic data, we quality-controlled the chemical features by retaining those above a sum relative abundance threshold of 10E-01 and present in at least 10% of all samples for each animal model individually. There were 267 and 374 such features in Ldlr-/- and ApoE-/- animals, respectively. Out of these, 137 metabolites were shared between the two models. Thus, the percentage shared between the animal models were 51% of total features in Ldlr-/- knockout models.Effect sizes were calculated over the individual genotype, mice, cage number, age, exposure type. For each of these covariates, we applied the mixed directional FDR methodology to test for the significance of each pairwise comparison among the groups. For each significant pairwise comparison via PERMANOVA , we computed the effect size using Cohen’s d or the absolute difference between the mean of each group divided by the pooled standard deviation. As diversity estimators we used unweighted UniFrac and Bray-Curtis distances matrices for the 16S rRNA sequencing and LC-MS/MS mass-spectrometry, respectively. For the microbiome data layer , when taking both genotypes together, we see that the first three largest effect sizes are mouse number, age and cage number, followed by genotype and exposure type.

It is important to note that the maximum difference on the first three covariates are related to genotype differences. For example, the maximum difference in mouse number is between two mice [mouse numbers 105 vs. 32 ; Figure 4.S1] that belong to two different genotypes and exposure types. To untangle the effect of genotype, we stratified our dataset by genotypes and calculated effect sizes of each of the covariates within each model. It is noteworthy that effects of covariates are ranked differently within each model, hinting towards underlying differences in the characteristics of the microbial community. Nevertheless, the effect of exposure is ranked comparably across models. Similarly, we calculate effect sizes of the above mentioned covariates for the metabolome data layer . When taking both genotypes together, consistent with the microbiome results, mouse number, age and cage number have the largest effect sizes, and the groups with the maximum effects belong to different genotypes [e.g. mouse number 114 vs. 17. We then stratified the data by genotype and observed that different covariates had distinct effects within each genotype. Interestingly, our analysis shows that unlike in Ldlr-/- mice, individual variability was not significant in ApoE-/- mice.Random Forest classifier was trained and evaluated with cross validation for each mouse model, using microbial or chemical features as predictors. During cross validation, all the samples from the same mouse appeared only in either training or validation data but not both to avoid over-optimistic cross-validation accuracy scores as a result of the classifier learning idiosyncrasies of the individual itself rather than the treatment. The classifiers trained for each mouse model were then applied on the samples of the other mouse model for cross-genotype prediction. For the longitudinal prediction, we trained and evaluated a RF classifier on the samples collected at each time point for AUC computation. To assess the capability of individual 16S sequences and metabolites to separate IHH-exposed from control animals,large pots plastic we used the abundance of each feature as the score to plot ROC curve and compute AUC, and highlighted the features that can single-handedly distinguish IHH on ROC plots. These analyses were done using the scikitlearn Python package.Molecular networking , introduced in 2012, was one of the first data organization approaches to visualize the relationships between fragmentation spectra for similar molecules from tandem mass spectrometry data in the context of metadata. It formed the basis for the web-based mass spectrometry infrastructure, Global Natural Products Social Molecular Networking  which sees ~200,000 new accessions per month. Molecular networking is used for a range of applications in drug discovery, environmental monitoring, medicine, and agriculture. While molecular networking is useful for visualizing closely related molecular families, the inference of chemical relationships at a dataset-wide level and in the context of diverse metadata requires complementary representation strategies. To address this need, we developed an approach that uses fragmentation trees and supervised machine learning to calculate all pairwise chemical relationships and visualizes it in the context of sample metadata and molecular annotations. We show that a chemical tree enables the application of various tree-based tools, originally developed for analyzing DNA sequencing data , for exploring mass-spectrometry data. We introduce Qemistree, pronounced chemis-tree, a software that constructs a chemical tree from fragmentation spectra based on predicted molecular fingerprints . Recent methods allow us to predict molecular fingerprints from tandem mass spectra . In Qemistree, we use SIRIUS and CSI:FingerID to obtain predicted molecular fingerprints. The users first perform feature detection to generate a list of observed ions, referred to as chemical features henceforth, to be analyzed by Qemistree .

SIRIUS then determines the molecular formula of each feature using the isotope and fragmentation patterns, and estimates the best fragmentation tree explaining the fragmentation spectrum. Subsequently, CSI:FingerID operates on the fragmentation trees using kernel support vector machines to predict molecular properties . We use these molecular fingerprints to calculate pairwise distances between chemical features that are hierarchically clustered to generate a tree representing their structural relationships. Although alternative approaches to hierarchically cluster features based on cosine similarity of fragmentation spectra exist , we use molecular fingerprints as it allows us to compare features based on a diverse range of structural properties predicted by CSI:FingerID. Additionally, as CSI:FingerID was shown to perform well for automatic in silico structural annotation , we leverage it to search molecular structural databases to provide complementary insights into structures when no match is obtained against spectral libraries. Subsequently, we use ClassyFire to assign a 5-level chemical taxonomyTo verify that molecular fingerprint-based trees correctly capture the chemical relationships between molecules, we generated an evaluation dataset with two human fecal samples, a tomato seedling sample, and a human serum sample. Mixtures of these samples were prepared by combining them in gradually increasing proportions to generate a set of diverse but related metabolite profiles and untargeted tandem mass spectrometry was used to profile the chemical composition of these samples. Mass-spectrometry was performed twice using different chromatographic gradients causing a non-uniform retention time shift between the two runs. The data processing of these two experiments leads to the same molecules being detected as different chemical features in downstream analysis. In Figure 5.1a we highlight how these technical variations make the same samples appear chemically disjointed.Using Qemistree, we map each of the spectra in the two chromatographic conditions to a molecular fingerprint, and organize these in a tree structure . Because molecular fingerprints are independent of retention time shifts, spectra are clustered based on their chemical similarity. This tree structure can be decorated using sample type descriptions, chromatographic conditions, and spectral library matches obtained from molecular networking in GNPS. Figure 5.1 shows that similar chemical features are detected exclusively in one of the two batches. However, based on the molecular fingerprints, these chemical features were arranged as neighboring tips in the tree regardless of the retention time shifts. This result shows how Qemistree can reconcile and facilitate the comparison of datasets acquired on different chromatographic gradients. We demonstrate the use of a chemical hierarchy in performing chemically informed comparisons of metabolomics profiles. In standard metabolomic statistical analyses, each molecule is assumed unrelated to the other molecules in the dataset.

The importance of microbes for xenobiotics metabolism was underscored by a study that demonstrated an increase in hepatic expression of ethanol metabolizing genes in germ-free mice, and exacerbation in hepatic steatosis . Non-alcoholic and alcoholic liver diseases are characterized by increased luminal and circulating levels of ethanol and its metabolites, acetaldehyde and acetate . These metabolites have independently been associated with liver damage . Acetaldehyde has been implicated in weakening the intestinal tight junctions, compromising the gut barrier and enabling translocation of microbial products . It has also been associated with down regulating the expression of antimicrobial peptides in the intestine , and eliciting inflammatory and adaptive host immune responses . Additionally, alcoholic liver disease is marked by reduced levels of intestinal butyrate , which is linked to weakening of intestinal tight junctions and, hence, permeability .NAFLD refers to a spectrum of liver disease that can be broadly classified into two categories: nonalcoholic fatty liver , the non-progressive form of NAFLD, and NASH, the progressive form of NAFLD . NASH is generally linked to type 2 diabetes mellitus, cardiovascular risk factors and obesity , although NAFLD has also been reported in lean individuals, emphasizing that genetic and environmental factors also contribute to disease development . Patients with NAFLD have a higher prevalence of SIBO and microbial dysbiosis . Using 16S amplicon sequencing, Boursier et al. found that the bacterial genera, Bacteroides and Ruminococcus were substantially increased, and Prevotella was reduced in patients with NASH compared to those without NASH. Loomba et al. utilized whole-genome metagenomics to characterize the gut microbiota in patients with NAFLD with and without advanced fibrosis and showed an increased abundance of Escherichia coli and Bacteroides vulgatus in patients with advanced fibrosis. An enrichment of Escherichiawas also seen in paediatric patients with NASH compared with children with obesity but without NASH .

Consistent with preclinical studies,growing blueberries in pots these studies indicate an association between Gram-negative bacteria and progression of liver fibrosis . Genetically modified mouse models have been used to study NAFLD-associated gut dysbiosis and permeability for mechanistic insights in liver disease progression. Rahman et al. used JAM-A -knockout mice to demonstrate that deficiency in this tight junction protein with a diet rich in saturated fats, fructose and cholesterol leads to increased intestinal permeability and liver inflammation. This inflammation could be alleviated by administering antibiotics, underscoring the importance of microbial translocation in promoting immune response in the liver. Another group used mice deficient in Muc2and found that there was a compensatory increase in intestinal levels of antimicrobial protein-coding genes, Reg3b and leading to an overall protective response against NAFLD . The contribution of liver-damaging inflammation in response to translocation of microbes and MAMPs has been elucidated . Using inflammasome-deficient mouse models , Henao-Mejia et al. conclude that there is an accumulation of MAMPs in portal circulation, which enhanced the expression of hepatic TNF, thereby promoting liver inflammation and NASH progression. Furthermore, cohousing inflammasome-deficient mice with wild-type controls exacerbated diet-induced hepatic steatosis and obesity in healthy cage mates, suggesting transferability of disease via the microbiota. Increasing links between NAFLD and the gut microbiome at both the observational and mechanistic levels make the gut microbiota an attractive source of biomarkers for early diagnosis of NAFLD. In a comparison between children with obesity with and without NASH, Zhu and colleagues observed markedly elevated gut microbial production of ethanol in those with NASH. Adults with NAFLD also show increased serum TMAO and hepatic bile acid synthesis , and decreased production of phosphatidylcholine . Furthermore, Loomba et al. observed differences in carbon and amino acid metabolism in gut microbiome of patients with NAFLDassociated advanced fibrosis . This proof-of-concept study provides preliminary evidence to support the utility of a microbiome-derived metagenomics signature to detect advanced fibrosis as well as candidacy for anti-fibrotic treatment trials in NAFLD.

The manifestation of ALD in patients who chronically abuse alcohol is a consequence of multifactorial interactions involving genetics, immune system, gut microbiome and environmental factors . Like NAFLD, the non-progressive form of ALD is characterized by accumulation of fat inside the liver , whereas the progressive form is marked by inflammation and liver injury . Our understanding of the compositional and mechanistic contributions of the gut microbiota in ALD is improving. As in NAFLD, SIBO has been demonstrated as an important hallmark of alcohol-associated liver disease in humans and mouse models . Intestinal dysbiosis in individuals who abuse alcohol is characterized by marked enrichment of Enterobactericaeae and reduction in abundances of Bacteroidetes and Lactobacillus. It has also been demonstrated that alcohol-induced dysbiosis is only partially reversible by alcohol withdrawal or probiotic treatment . Interestingly, patients dependent on alcohol also displayed reduced fungal diversity and Candida overgrowth, presenting the first evidence of the role of gut mycobiome in pathogenesis of liver diseases . Genetically modified murine models have advanced our mechanistic understanding of the contribution of various components of the gut-barrier in the etiology and progression of ALD. Using Reg3b-/- or Reg3g-/- mice, it was found that REG3 lectins protected against alcoholic steatohepatitis by reducing mucosa-associated microbiota, thereby preventing translocation of viable bacteria . Muc2-deficient mice were protected against alcohol-induced liver inflammation due to a compensatory increase in Reg3g and Reg3b lectins . Furthermore, IgA-knockout in mice led to increased levels of IgM and a net protective effect against ASH progression . In response to ethanol-induced gut-barrier dysfunction and translocation, TLRs and other PRRs activate hepatic Kupffer cells and macrophages, as was demonstrated in male Wistar rats . This step initiates inflammatory cascades releasing TNF, IL-1, IL-10, IL-12 and TGF-β . Using TLR4 chimeric mice, it was shown that endotoxin-induced release of TGF-β is mediated by a MyD88-NF-κB-dependent pathway, providing an explanatory mechanism for endotoxin-induced liver inflammation . Furthermore, increased translocation of fungal β- glucan also induced liver inflammation via CLEC7A receptor on hepatic Kupffer cells such that treatment of mice with antifungal agents reduced intestinal fungal overgrowth, decreased β-glucan translocation and ameliorated ethanol-induced liver disease .

Alongside immunological responses to barrier dysfunction, ALD is also marked by systemwide changes in many bio-active compounds. Alcohol consumption leads to an increase in hepatic bile acid synthesis in humans and mice .This increase could be explained by dysbiosis associated disruption in FXR activation in enterocytes as FXR-deficient mice were more likely to develop ethanol-induced steatohepatitis , and treatment with an FXR agonist had protective effects against liver damage . Alcohol-associated dysbiosis in mice was further linked to reduced LCFA biosynthesis such that LCFA supplementation restored eubiosis. In fact, a statistically significant correlation between Lactobacillus spp. and bacterial LCFA was found in patients with ALD but not in healthy individuals as controls . Butyrate production was also negatively altered following ethanol exposure and administration of butyrate in the form of tributyrin mitigated alcohol-induced liver injury in mice .With increasing evidence of mechanistic links between the gut microbiota and liver disease progression, fecal microbiota transplantation is being explored as a therapeutic option for ALD . However, larger, carefully designed trials across multiple ethnic groups are needed before FMT can be considered safe in routine clinical practice for managing ALD.Cirrhosis is an extreme manifestation of chronic liver injury characterized by loss of liver cells, thick fibrous scar and regenerating nodules; this topic has been extensively reviewed elsewhere so we only provide a brief discussion here . NAFLD, ALD, primary biliary cholangitis , primary sclerosing cholangitis or hepatitis can each progress to cirrhosis and constitute its subtypes. ASH and NASH have emerged as the second and third leading causes of cirrhosis in adults in the USA and based on the etiology there is a variable risk of developing HCC . Alterations in the gut microbiota including dysbiosis and SIBO have been associated with and its complications . Treatment for portal systemic encephalopathy and decompensated cirrhosis includes treatment with nonsystemic antibiotics such as rifaximin to reduce intestinal microbiota overgrowth . Gut microbiome alterations were observed in patients with alcohol-associated and hepatitis-associated cirrhosis in a Chinese cohort ,drainage gutter with an invasion of the lower intestinal tract by microbes associated with the oral cavity such as Veillonella and Steptococcus. Concordant with these findings, Chen and colleagues also found an over-representation of genera including Veillonella, Megasphaera, Dialister, Atopobium and Prevotella in the duodenum of patients with cirrhosis. The genera Neisseria and Gemella were discriminative between HBV-related and PBC-related cirrhosis . In 2017, Bajaj and colleagues observed statistically significant fungal dysbiosis in patients with cirrhosis and showed that Bacteroidetesto Ascomycota ratio could independently predict hospitalization in these patients . All experimental models of liver fibrosis result in gut microbial dysbiosis and increased intestinal permeability, and treatment of gastrointestinal tract with nonabsorbable antibiotics improved survival by immunomodulation, reducing translocation and incidences of infection . Mice with genetic ablations of the receptors for bacterial product ligands are protected from experimental liver fibrosis . The current treatment philosophy involves decreasing the bacterial product ligands or blocking their receptors, which results in decreased inflammatory and fibrogenic signaling in the liver, although no antifibrotic drug is currently available for routine clinical practice.The etiology of non-viral HCC follows a so-called multiplehit pathway, whereby liver steatosis, followed by oxidative stress, ER stress together with intestinal dysbiosis and inflammation contribute to the final manifestation of cancer.

The gut microbiota dramatically changes in composition in hosts with HCC. Clostridium species have been found to be enriched in obesity-induced mouse models of HCC , but clinical studies of patients with HCC detected an overgrowth of intestinal Escherichia coli . Murine models and human studies have reported a migration of Helicobacter species to HCC tumor tissues . Notably, members of this genus are known to promote tumor-development by activating NF-kB and WNT signaling and suppressing anti-tumor immunity, and might have a potential role in HCC development . To get insights into the molecular events explaining the progression of liver disease to HCC, various murine models have been explored. However, most of these models have proven suboptimal because they either do not develop all intermediate pathological & metabolic stages, or they manifest HCC incompletely . We have highlighted some frequently-used rodent models of liver disease, their usage and caveats in Table 1.2.2 to aide future research. Accumulating evidence suggests that HCC-associated dysbiosis is accompanied by gutbarrier dysfunction, bacterial translocation, systemic circulation of their tumor-promoting metabolites and activation of proinflammatory and oncogenic signaling pathways . The intestinal poly-immunoglobulin receptor regulates the transport of IgA into the intestinal lumen and maintains microbial homeostasis . PIgR-/- mice modelling NASH-induced HCC had increased levels of systemic and liver IgA, and a concomitant increase in hepatic tumorigenesis due to localized inhibition of liver cytotoxic T cells that prevent HCC development . Furthermore, the application of broad spectrum antibiotics has been shown to attenuate liver inflammation and HCC-development in mice , highlighting the role of the intestinal microbiome in liver tumorigenesis. In another mouse model in which HCC was induced by diethylnitrosamine , activation of TLR4 due to LPS translocation upregulated the hepatic mitogen EREG in hepatic stellate cells and activated NF-kB, resulting in enhanced tumor cell proliferation . Additionally, the secondary bile acid deoxycholic acid , a metabolic byproduct of gut bacteria, was shown to upregulate proinflammatory genes, such as IL6 and TNF, to provoke a senescence associated secretory phenotype in hepatic stellate cells suggesting that SASP could be playing a key role in at least obesity-linked HCC development . In addition to its role in HCC development, the gut microbiome also modulates protumorigenic adaptive immune response via type 17 T helper cells, which produce the proinflammatory cytokine IL-17A . The therapeutic efficacy of the anticancer drugcyclophosphamide depended on the interplay between Th17 signaling and gut microbiome such that germ-free tumor-bearing mice or mice given non-absorbable antibiotics had reduced Th17 response and a subsequent resistance to therapeutic effects of cyclophosphamide was seen . Increased understanding of the role of the gut microbiota has motivated successful microbiome-based therapeutic modalities for HCC, such as treatment with synthetic bile acids to reduce HCC risk in patients with NAFLD , non-selective beta-blockers in the intestinal mucosa which prevent bacterial translocation and liver inflammation and administration of probiotics in rodents models of HCC slowed tumor growth and reduced tumor size .

The LPP had an extraction rate comparable to the SPP, showing that the particle size had no significant effect on the extraction rate. In summary, when using WPP for antioxidant extraction, higher TEY, TPY, and TPC can be achieved by increasing the extraction temperature, time, and solvent ratio. The DSA was independent of the extraction time and solvent ratio but decreased with the increase in extraction temperature. The two groups of peel particles, with average particle sizes of 0.60 and 0.38 mm, respectively, had no significantly different effects on the extraction of phenolics with varied extraction temperature, time, and solvent ratio. The highest TEY, TPY, and TPC obtained were 57.83%, 12.80%, and 22.06%, respectively. The DSA ranged from 5.37 to 6.35 g g-1. The results indicated that extraction of phenolics from peel particles, produced by grinding to less than 0.6mm with a large cutting head, at a temperature of 20°C for 6 min using a solvent ratio of 4:1 could be the most economical and sustainable approach for industrial-scale production. The chromatogram obtained from the HPLC, showing the peaks of major compounds in the peel extract, including gallic acid, ellagic acid, punicalagin , and punicalagin , is shown in Figure 2.5 a. The contents of the four major phenolic compounds produced by the five groups of extraction conditions are shown in Figure 2.5 b. The gallic acid content significantly improved, from 0.17 to 0.29 mg g-1 , with the increase in solvent ratio from 1:1 to 4:1. Except for the group with a 1:1 solvent ratio , the gallic acid contents obtained with the other groups with different solvent ratios varied from 0.27 to 0.35 mg g-1 and were not significantly different, regardless of the time and temperature. The ellagic acid content varied from 0.77 to 1.51 mg g-1, with no significant differences among groups G3, G4, and G5. The solvent ratio mostly influenced punicalagin. At the same extraction conditions, the punicalagin content increased from 2.13 to 4.48 mg g-1 when the solvent ratio increased from 1:1 to 8:1. In addition to the solvent ratio ,snap clamps ABS pvc pipe clip the extraction time and temperature affected the extraction of punicalagin , which can be seen from the increased punicalagin content from 7.51 mg g-1 to 9.17 mg g-1 .

The punicalagin purity ranged in order of G2 > G4 > G5 > G3 > G1, and the corresponding values were 88.99%, 88.27%, 87.73%, 87.64%, and 85.93%, respectively. Qu et al. compared the gallic acid, punicalagin, punicalagin , and ellagic acid concentrations of different pomegranate products. The results presented in this study showed significantly higher retention of punicalagin than the pomegranate peel extract using dried peel particles used by Qu et al. . The WPP extraction in this study also achieved slightly higher phenolic concentrations compared to Langers 100% pomegranate juice. To study the effects of drying, DPP was produced using HA drying and IR drying, and the peel compositions and phenolic extraction conditions were compared between DPP and WPP. The compositions of WPP and DPP on a dry basis are shown in Table 2.5 Composition of fresh and hot-air dried pomegranate peel. . The WPP had higher contents of protein, ash, and crude fat than the DPP. The loss of these contents was reduced by avoiding the drying process. On the other hand, the HA DPP maintained higher total dietary fiber at 25.44%, and the ratio of insoluble dietary fiber to soluble dietary fiber was 8.84. This was higher than the values for WPP, which maintained 17.19% TDF and an IDF/SDF ratio of 4.93. Morais et al. compared the compositions of raw, freeze-dried, and oven-dried papaya peels. They reported similar findings for the differences in fiber content, but the differences were not statistically significant. Figure 2.6 shows the TEY, TPY, DSA, and color characteristics of IR DPP, HA DPP, and WPP. The DPP resulted in significantly lower TEY, TPY, and TPC than the WPP. The DSA values were similar for both DPP and WPP at about 6.41 g g-1. In other words, extraction from WPP resulted in 10% more extract yield and 2.5% more TPY with similar DSA compared to DPP. Loizzo et al. investigated the phytochemical contents of extracts from fresh and processed peel and pulp. Compared to steamed, baked, and microwaved pulp, extraction with fresh pulp achieved up to 0.9% higher TEY and twice the TPC. Their results demonstrated that extraction with fresh peel or pulp could reduce the phytochemical loss that occurs during the drying process. Similarly, Mphahlele et al. compared the bio-active compounds in fresh peel and hot-air dried peel at 40°C, 50°C, and 60°C. As for color, extraction of WPP achieved significantly higher L* , a* , b* , and C* values.

The results demonstrated statistically higher retention of L* and a* values using WPP. According to Cadena et al. , changed color characteristics indicate the formation of caramel-colored pigments resulting from nonenzymatic processes, which are related to lower sensory acceptance. Therefore, extraction from WPP could be a more suitable method for the extraction of polyphenols for use in food product development and supplementation. PCA was applied to explore the interdependence among variables. Observations consisted of the average sub-sampling results from the 30 aforementioned extraction conditions at different extraction times, temperatures, and solvent ratios. Four vectors were estimated based on the eigenvectors of the correlation matrix of four variables: total extract yield , total phenolic yield , total phenolic content , and DPPH scavenging activity . The eigenvalues of F1 to F4 were 2.548, 0.899, 0.544, and 0.008, and the first three PCs accounted for 63.70%, 22.48%, and 13.61% of the sample variance, respectively, and represented 99.79% of the total variance in cumulation . Biplots of the observations and variables show the data distributions of F1-F2 and F1-F3. Confidence ellipses with 99% confidence intervals were used for each set of experiment groups, and no outliers were detected. PCA weighting scores of the four measured variables are listed in Table 2.6. For instance, TEY and TPC were positively correlated with the F1 axis, whereas TPY and DSA were negatively correlated. In addition, TEY and TPY were positively correlated with the F2 axis, while DSA was negatively correlated with the F3 axis. Figure 2.7 also shows the data distribution for F1-F2 and F1-F3. For instance, the data point with a higher F1-axis value had higher TPC, which was extracted at 60°C for 6 min using a solvent ratio of 8:1. This was following the experimental results, indicating that PCA can be applied for future condition prediction. Extraction of bio-active compounds from waste fruit peel is an efficient approach to improve food system sustainability and industry profitability.

This study developed a novel green process for antioxidant extraction from wet pomegranate peel and investigated the effects of extraction conditions on polyphenol yield and quality, including phenolic composition, DPPH scavenging activity, and color characteristics. PCA condensed the multivariable analysis into three factors, which explained 99.79% of the variance and could be suitable for future process development. Three parameters, including drying preparation, extraction temperature, and solvent ratio, significantly influenced the extraction rate. Considering water usage and energy consumption, WPP extraction at 20°C for 6 min with a solvent ratio of 4:1 is recommended as an economic and sustainable process, resulting in 10.53% total phenolic yield with 88.93% punicalagin purity. Overweight is raising concern worldwide due to its high prevalence and various adverse health outcomes. According to a report from World Health Organization, an adult with Body Mass Index between 25.0 to 30.0 is defined as overweight, and over 1.9 billion adults worldwide were overweight in 2016, accounting for 39% of the population . Being overweight can further induce obesity when BMI increased beyond 30.0. These two statuses are major risk factors of physical and mental illness. Wilson et al. conducted 44-year follow-up research on 5209 participants aged 30 to 62 years from the Framingham cohort . Results showed that being overweight was related to elevated cardiovascular risks, including hypertension , angina pectoris , and coronary heart disease . Calle and Kaaks reviewed obesity and obese-related epidemiological studies. An increased risk of cancers was noted from 1.2-2 folds, including colorectal, endometrial, kidney, and oesophageal cancer . BeLue et al. studied the relation between mental healthiness and overweight in youth aged 12 to years in different races and ethnicity . Their results revealed that overweight white and Hispanic youth possessed a higher percentage of self-reported depression, anxiety,greenhouse snap clamps and other mental and behavioral problems. Various causes contributed to being overweight. Among them, a calorie-dense and nutrient-poor diet is a major contributor along with a lack of exercise. Standard American Diet is a typical western diet that includes excess natural and added carbohydrates, fats, and sodium while lacking in consumption of fruits, vegetables, and whole grains . Improving the diet pattern for weight control is in need. Diet with the addition of phytochemicals, such as polyphenol, demonstrated positive health outcomes on weight management. Studies have suggested that polyphenol modulated the plasma and hepatic cholesterol in a few possible mechanisms, including inhibiting enzymes related to intestinal carbohydrate digestion and glucose absorption , inhibiting pancreatic lipase activity and fat absorption from the intestine , promoting β-oxidation of fatty acids , increasing bile excretion to eliminate the cholesterol , and regulating the gut microbiota towards a leaner composition .

Pomegranate peel is a common underused fruit by-product from the juicing process and consists of up to 53.01% of the fruit weight . The high molecular weight polyphenols in the pomegranate peel are the major high-value phytochemicals and have been proven associated with reduced risks of chronic diseases , including type 2 diabetes and cardiovascular diseases . Among all the polyphenols in pomegranate peel, gallic acid , ellagic acid , punicic acid, and punicalagin-α, -β are responsible for most health benefits . It was worth noting that punicalagin is unique in pomegranate peel and demonstrated the greatest antioxidant activities with abundant hydroxyl groups, which can trap peroxyl radicals to reduce oxidation . Therefore, pomegranate peel is a promising source for polyphenols. By far, nearly all the studies of health benefits in pomegranate peel utilized liquid extractable polyphenol. Limited research focused on the pomegranate peel as a whole. Labib and Hossin characterized the effects of pomegranate peel powders and extracts on obese hypercholesterolemic rats solely from anthropometric and serum lipid. Insights of hepatic lipid profile were missing and the regulating mechanisms were not investigated in their study . Moreover, research has shown that the polyphenol and fiber in the food matrix might have a synergistic effect to promote health . Therefore, the objectives of this research were to compare the hypolipidemic properties of PPP and PPE and investigate the regulating mechanisms by supplementing the high-fat diets with different percentages of PPP and PPE to male Syrian hamsters. Pomegranate peel of Wonderful variety was collected from a juicing plant located in Buttonwillow, California in October of 2017. The peel was processed based on Wu et al. . In summary, the peel was sliced and ground into particles less than 0.6 mm. Then extract was obtained by mixing the peel particles with 4 times of water at 20 ⁰C for 6 mins, then filtered before administration to the hamsters. The male Syrian hamster was used since it possessed similarities of hepatic cholesterol and bile acid metabolism with humans compared to other rodents . The compositions of peel powder and extract were listed in Table 2.5. The study was approved by the Animal Care and Use Committee, Western Regional Research Center, USDA, Albany, CA, USA. 45 male golden hamsters were acclimatized for 2 weeks. They were fed with Purina Rodent Laboratory Chow and individually raised in a 20−22 °C environment with relative humidity at 60 %, and 12 h alternating light/dark cycle. After that, 45 hamsters were randomly divided into five groups for each diet as indicated in. A high-fat diet with 20% fat energy intake was set as a control group. 5 and 10% of lyophilized PPP were supplemented into the HF diet ad libitum to evaluate the dose effects. In correspondence, 2.5 and 5% of lyophilized PPE addition were applied to investigate the effect of supplementation form. In this way, LP/LE group contained nearly 8.68 mg soluble phenolic compounds per kg body weight, and HP/HE group doubled the content. These dosages corresponded to approximately 70 mg and 140 mg per day in a 60 kg human according to the Km factor ratio of 5 and 37 for hamsters and humans , respectively .