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Comparing the appearance and phytochemical characterization of dried lily (L. davidii var. unicolor) bulbs processed by different drying technologies

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  • Lily bulbs are valued for their health benefits, and drying is a common method for their preservation. This study employed untargeted metabolomics using UHPLC-QTOF-MS to analyze the phytochemical profiles of lily bulbs dried by hot air (HD), microwave (MD), and vacuum freeze (FD) methods. In terms of appearance, FD samples exhibited minimal browning and wrinkling, while HD bulbs showed the most severe changes. Nineteen potential markers were identified, with HD samples showing higher levels of bitter amino acids, peptides, and N-fructosyl phenylalanine. The markers of FD samples were glutamine, coumarin, and p-coumaric acid. Notably, eleutheroside E was detected in lily bulbs for the first time and confirmed as an MD marker, with levels 1.51-fold and 6.19-fold higher than in FD and HD samples, respectively. MD method shows promise for enriching bioactive compounds in dried lily bulbs.
  • The Fabaceae family, the third largest family in angiosperms, contains about 24,480 species (WFO, https://wfoplantlist.org), and has been a historically important source of food crops[14]. Peas (formerly Pisum sativa L. renamed to Lathyrus oleraceusPisum spp. will be used hereafter due to historical references to varietal names and subspecies that may not have been fully synonymized), are a member of the Fabaceae family and is among one of the oldest domesticated food crops with ongoing importance in feeding humans and stock. Peas originated in Western Asia and the Mediterranean basin where early finds from Egypt have been dated to ~4500 BCE and further east in Afghanistan from ~2000 BCE[5], and have since been extensively cultivated worldwide[6,7]. Given that peas are rich in protein, dietary fiber, vitamins, and minerals, have become an important part of people's diets globally[810].

    Domesticated peas are the result of long-term human selection and cultivation, and in comparison to wild peas, domesticated peas have undergone significant changes in morphology, growth habits, and yield[1113]. From the long period of domestication starting in and around Mesopotamia many diverse lineages of peas have been cultivated and translocated to other parts of the world[14,15]. The subspecies, Pisum sativum subsp. sativum is the lineage from which most cultivars have been selected and is known for possessing large, round, or oval-shaped seeds[16,17]. In contrast, the subspecies, P. sativum subsp. elatius, is a cultivated pea which more closely resembles wild peas and is mainly found in grasslands and desert areas in Europe, Western Asia, and North Africa. Pisum fulvum is native to the Mediterranean basin and the Balkan Peninsula[15,18], and is resistant to pea rust caused by the fungal pathogen Uromyces pisi. Due to its resistance to pea rust, P. fulvum has been cross-bred with cultivated peas in the development of disease-resistant strains[19]. These examples demonstrate the diverse history of the domesticated pea and why further study of the pea pan-plastome could be employed for crop improvement. While studies based on the nuclear genome have been used to explore the domestication history of pea, these approaches do not account for certain factors, such as maternal inheritance. Maternal lineages, which are inherited through plastomes, play a critical role in understanding the full domestication process. A pan-plastome-based approach will no doubt allow us to investigate the maternal genetic contributions and explore evolutionary patterns that nuclear genome studies may overlook. Besides, pan-plastome analysis enables researchers to systematically compare plastome diversity across wild and cultivated species, identifying specific regions of the plastome that contribute to desirable traits. These plastid traits can then be transferred to cultivated crops through introgression breeding or genetic engineering, leading to varieties with improved resistance to disease, environmental stress, and enhanced agricultural performance.

    Plastids are organelles present in plant cells and are the sites in which several vital biological processes take place, such as photosynthesis in chloroplasts[2024]. Because the origin of plastids is the result of an ancient endosymbiotic event, extant plastids retain a genome (albeit much reduced) from the free-living ancestor[25]. With the advancement of high-throughput DNA sequencing technology, over 13,000 plastid genomes or plastomes have been published in public databases by the autumn of 2023[24]. Large-scale comparison of plastomic data at multiple taxonomic levels has shown that plastomic data can provide valuable insights into evolution, interspecies relationships, and population genetic structure. The plastome, in most cases, displays a conserved quadripartite circular genomic architecture with two inverted repeat (IR) regions and two single copy (SC) regions, referred to as the large single-copy (LSC) and small single-copy (SSC) regions. However, some species have lost one copy of the inverted repeated regions, such as those in Erodium (Geraniaceae family)[26,27] and Medicago (Fabaceae)[28,29]. Compared to previous plastomic studies based on a limited number of plastomes, the construction of pan-plastomes attempts to describe all nucleotide variants present in a lineage through intensive sampling and comparisons. Such datasets can provide detailed insights into the maternal history of a species and help to better understand applied aspects such as domestication history or asymmetries in maternal inheritance, which can help guide future breeding programs. Such pan-plastomes have recently been constructed for several agriculturally important species. A recent study focuses on the genus Gossypium[20], using plastome data at the population level to construct a robust map of plastome variation. It explored plastome diversity and population structure relationships within the genus while uncovering genetic variations and potential molecular marker loci in the plastome. Besides, 65 samples were combined to build the pan-plastome of Hemerocallis citrina[30] , and 322 samples for the Prunus mume pan-plastome[31]. Before these recent efforts, similar pan-plastomes were also completed for Beta vulgaris[32], and Nelumbo nucifera[33]. However, despite the agricultural importance of peas, no such pan-plastome has been completed.

    In this study, 103 complete pea plastomes were assembled and combined another 42 published plastomes to construct the pan-plastome. Using these data, the following analyses were conducted to better understand the evolution and domestication history of pea: (1) genome structural comparisons, (2) codon usage bias, (3) simple sequence repeat patterns, (4) phylogenetic analysis, and (5) nucleotide variation of plastomes in peas.

    One hundred and three complete pea plastomes were de novo assembled from public whole-genome sequencing data[34]. For data quality control, FastQC v0.11.5 (www.bioinformatics.babraham.ac.uk/projects/fastqc/) was utilized to assess the quality of the reads and ensure that the data was suitable for assembly. The clean reads were then mapped to a published pea plastome (MW308610) plastome from the GenBank database (www.ncbi.nlm.nih.gov/genbank) as the reference using BWA v0.7.17[35] and SAMtools v1.9[36] to isolate plastome-specific reads from the resequencing data. Finally, these plastome-specific reads were assembled de novo using SPAdes v3.15.2[37]. The genome annotation was conducted by Geseq online program (https://chlorobox.mpimp-golm.mpg.de/geseq.html). Finally, the OGDRAW v1.3.1[38] program was utilized to visualize the circular plastome maps with default settings. To better resolve the pan-plastome for peas, 42 complete published pea plastomes were also downloaded from NCBI and combined them with the de novo data (Supplementary Table S1).

    To investigate the codon usage in the pan-plastome of pea, we utilized CodonW v.1.4.2 (http://codonw.sourceforge.net) to calculate the Relative Synonymous Codon Usage (RSCU) value of the protein-coding genes (PCGs) longer than 300 bp, excluding stop codons. The RSCU is a calculated metric used to evaluate the relative frequency of usage among synonymous codons encoding the same amino acid. An RSCU value above 1 suggests that the codon is utilized more frequently than the average for a synonymous codon. Conversely, a value below 1 indicates a lower-than-average usage frequency. Besides, the Effective Number of Codons (ENC) and the G + C content at the third position of synonymous codons (GC3s) were also calculated in CodonW v.1.4.2. The ENC value and GC3s value were utilized for generating the ENC-GC3s plot, with the expected ENC values (standard curve), are calculated according to formula: ENC = 2 + GC3s + 29 / [GC3s2 + (1 – GC3s)2][39].

    The MISA program[40] was utilized to detect simple sequence repeats (SSRs), setting the minimum threshold for repeat units at 10 for mono-motifs, 6 for di-motifs, and 5 for tri-, tetra-, penta-, and hexa-motif microsatellites, respectively.

    The 145 complete pea plastomes were aligned using MAFFT v 7.487[41]. Single nucleotide variants (SNVs)-sites were used to derive an SNV only dataset from the entire-plastome alignment[42]. A total of 959 SNVs were analyzed using IQ-TREE v2.1[43] with a TVMe + ASC + R2 substitution model, determined by ModelTest-NG[44] based on BIC, and clade support was assessed with 1,000 bootstrap replicates. Vavilovia formosa (MK604478) was chosen as an outgroup. The principal coordinates analysis (PCA) was conducted in TASSEL 5.0[45].

    DnaSP v6[46] was utilized to identify different haplotypes among the plastomes, with gaps and missing data excluded. Haplotype networks were constructed in Popart v1.7[47] using the median-joining algorithm. Haplotype diversity (Hd) for each group was calculated by DnaSP v6[46], and the evolutionary distances based on the Tamura-Nei distance model were computed based on the population differentiation index (FST) between different groups with the plastomic SNVs.

    In this study, the pan-plastome structure of peas was elucidated (Fig. 1). The length of these plastomes ranged from 120,826 to 122,547 bp. And the overall GC content varied from 34.74% to 34.87%. In contrast to typical plastomes characterized by a tetrad structure, the plastomes of peas contained a single IR copy. The average GC content among all pea plastomes was 34.8%, with the highest amount being 34.84% and the lowest 34.74%, with minimal variation among the pea plastomes.

    Figure 1.  Pea pan-plastome annotation map. Indicated by arrows, genes listed inside and outside the circle are transcribed clockwise and counterclockwise, respectively. Genes are color-coded by their functional classification. The GC content is displayed as black bars in the second inner circle. SNVs, InDels, block substitutions and mixed variants are represented with purple, green, red, and black lines, respectively. Single nucleotide variants (SNVs), block substitutions (BS, two or more consecutive nucleotide variants), nucleotide insertions or deletions (InDels), and mixed sites (which comprise two or more of the preceding three variants at a particular site) are the four categories into which variants are divided.

    A total of 110 unique genes were annotated (Supplementary Table S2), of which 76 genes were PCGs, 30 were transfer RNA (tRNA) genes and four were ribosomal RNA (rRNA) genes. Genes containing a single intron, include nine protein-coding genes (rpl16, rpl2, ndhB, ndhA, petB, petD, rpoC1, clpP, atpF) and six tRNA genes (trnK-UUU, trnV-UAC, trnL-UAA, trnA-UGC, trnI-GAU, trnG-UCC). Additionally, two protein-coding genes ycf3 and rps12 were found to contain two introns.

    The codon usage frequency in pea plastome genes is shown in Fig. 2a. The analysis of codon usage in the pea plastome indicated significant biases for specific codons across various amino acids. Here a nearly average usage in some amino acids was observed, such as Alanine (Ala) and Valine (Val). For most amino acids, the usage of different synonymous codons was not evenly distributed. Regarding stop codons, a nearly even usage was found, with 37.0% for TAA, 32.2% for TAG and 30.8% for TGA.

    Figure 2.  (a) The overall codon usage frequency in 51 CDSs (length > 300 bp) from the pea pan-plastome. (b) The heatmap of RSCU values in 51 CDSs (length > 300 bp) from the pea pan-plastome. The x-axis represents different codons and the y-axis represents different CDSs. The tree at the top was constructed based on a Neighbor-Joining algorithm.

    The RSCU heatmap (Fig. 2b) showed different RSCU values for all codons in plastomic CDSs. In general, a usage bias for A/T in the third position of codons was found among CDSs in the pea pan-plastome. The RSCU values among these CDSs ranged from 0 to 4.8. The highest RSCU value (4.8) was found with the CGT codon in the cemA gene, where six synonymous codons exist for Arg but only CGT (4.8) and AGG (1.2) were used in this gene. This explained in large part the extreme RSCU value for CGT, resulting in an extreme codon usage bias in this amino acid.

    In the ENC-GC3s plot (Fig. 3), 31 PCGs were shown below the standard curve, while 20 PCGs were above. Besides, around 12 PCGs were near the curve, which meant these PCGs were under the average natural selection and mutation pressure. This plot displayed that the codon usage preferences in pea pan-plastomes were mostly influenced by natural selection. Five genes were shown an extreme influence with natural selection for its extreme ΔENC (ENCexpected – ENC) higher than 5, regarding as petB (ΔENC = 5.18), psbA (ΔENC = 8.96), rpl16 (ΔENC = 5.62), rps14 (ΔENC = 14.29), rps18 (ΔENC = 6.46) (Supplementary Table S3).

    Figure 3.  The ENC-GC3s plot for pea pan-plastome, with GC3s as the x-axis and ENC as the y-axis. The expected ENC values (standard curve) are calculated according to formula: ENC = 2 + GC3s + 29 / [GC3s2 + (1 − GC3s)2].

    For SSR detection (Fig. 4), mononucleotide, dinucleotide, and trinucleotide repeats were identified in the pea pan-plastome including A/T, AT/TA, and AAT/ATT. The majority of these SSRs were mononucleotides (A/T), accounting for over 90% of all identified repeats. Additionally, we observed that A/T and AT/TA repeats were present in all pea accessions, whereas only about half of the plastomes contained AAT/ATT repeats. It was also found that the number of A/T repeats exhibited the greatest diversity, while the number of AAT/ATT repeats showed convergence in all plastomes that possessed this repeat.

    Figure 4.  Simple sequence repeats (SSRs) in the pea pan-plastome. The x-axis represents different samples of pea and the y-axis represents the number of repeats in this sample. (a) The number of A/T repeats in the peapan-plastome. (b) The number of AT/TA and AAT/ATT repeats of pea pan-plastomes.

    To better understand the phylogenetic relationships and evolutionary history of peas, a phylogenetic tree was reconstructed using maximum likelihood for 145 pea accessions utilizing the whole plastome sequences (Fig. 5a). The 145 pea accessions were grouped into seven clades with high confidence. These groups were named the 'PF group', 'PSeI-a group', 'PSeI-b group', 'PA group', 'PSeII group', 'PSeIII group', and the 'PS group'. The naming convention for these groups relates to the majority species names for accessions in each group, where P. fulvum makes up the 'PF group', P. sativum subsp. elatius in the 'PSeI-a group', 'PSeI-b group', 'PSeII group', and 'PSeIII group', P. abyssinicum in the 'PA group', and P. sativum in the 'PS group'. From this phylogenetic tree, it was observed that the 'PSeI-a group' and the 'PSeI-b group' had a close phylogenetic relationship and nearly all accessions in these two groups (except DCG0709 accession was P. sativum) were identified as P. sativum subsp. elatius. In addition to the P. sativum subsp. elatius found in PSeI, seven accessions from the PS group were identified as P. sativum subsp. elatius.

    The PCA results (Fig. 5b) also confirmed that domesticated varieties P. abyssinicum were closer to cultivated varieties PSeI and PSeII, while PSeIII was more closely clustered with cultivated varieties of P. sativum. A previous study has indicated that P. sativum subsp. sativum and P. abyssinicum were independently domesticated from different P. sativum subsp. elatius populations[34].

    The complete plastome sequences were utilized for haplotype analysis using TCS and median-joining network methods (Fig. 5c). A total of 76 haplotypes were identified in the analysis. The TCS network resolved a similar pattern as the other analyses in that six genetic clusters were resolved with genetic clusters PS and PSeIII being very closely related. The genetic cluster containing P. fulvum exhibits greater genetic distance from other genetic clusters. The genetic clusters containing P. abyssinicum (PA) and P. sativum (PS) had lower levels of intracluster differentiation. In the TCS network, Hap30 and Hap31 formed distinct clusters from other haplotypes, such as Hap27, which may account for the genetic difference between the 'PSeI-a group' and 'PSeI-b group'. The network analysis results were consistent with the findings of the phylogenetic tree and principal component analyses results in this study.

    Figure 5.  (a) An ML tree resolved from 145 pea plastomes. (b) PCA analysis showing the first two components. (c) Haplotype network of pea plastomes. The size of each circle is proportional to the number of accessions with the same haplotype. (d) Genetic diversity and differentiation of six clades of peas. Pairwise FST between the corresponding genetic clusters is represented by the numbers above the lines joining two bubbles.

    Among the six genetic clusters, the highest haplotype diversity (Hd) was observed in PSeIII (Hd = 0.99, π = 0.22 × 10−3), followed by PSeII (Hd = 0.96, π = 0.43 × 10−3), PSeI (Hd = 0.96, π = 0.94 × 10−3), PF (Hd = 0.94, π = 0.6 × 10−4), PS (Hd = 0.88, π = 0.3 × 10−4), and PA (Hd = 0.70, π = 0.2 × 10−4). Genetic differentiation was evaluated between each genetic cluster by calculating FST values. As shown in Fig. 5d, except for the relatively lower population differentiation between PS and PSeIII (FST = 0.54), and between PSeI and PSeII (FST = 0.59), the FST values between the remaining clades ranged from 0.7 to 0.9. The highest population differentiation was observed between PF and PA (FST = 0.98). The FST values between PSeI and different genetic clusters were relatively low, including PSeI and PF (FST = 0.80), PSeI and PS (FST = 0.77), PSeI and PSeIII (FST = 0.72), PSeI and PSeII (FST = 0.59), and PSeI and PA (FST = 0.72).

    To further determine the nucleotide variations in the pea pan-plastome, 145 plastomes were aligned and nucleotide differences analyzed across the dataset. A total of 1,579 variations were identified from the dataset (Table 1), including 965 SNVs, 24 Block Substitutions, 426 InDels, and 160 mixed variations of these three types. Among the SNVs, transitions were more frequent than transversions, with 710 transitions and 247 transversions. In transitions, T to G and A to C had 148 and 139 occurrences, respectively, while in transversions, G to A and C to T had 91 and 77 occurrences, respectively.

    Table 1.  Nucleotide variation in the pan-plastome of peas.
    Variant Total SNV Substitution InDel Mix
    (InDel, SNV)
    Mix
    (InDel, SUB)
    Total 1,576 965 24 426 156 4
    CDS 734 445 6 176 103 4
    Intron 147 110 8 29 0 0
    tRNA 20 15 1 4 0 0
    rRNA 11 3 0 6 2 0
    IGS 663 392 9 211 51 0
     | Show Table
    DownLoad: CSV

    When analyzing variants by their position to a gene (Fig. 6), there were 731 variations in CDSs, accounting for 46.3% of the total variations, including 443 SNVs (60.6%), six block substitutions (0.83%), 175 InDels (23.94%), and four mixed variations (14.64%). There were 104 variants in introns, accounting for 6.59% of the total variations, including 78 SNVs (75%), seven block substitutions (6.73%), and 19 InDels (18.27%). IGS (Intergenic spacers) contained 660 variations, accounting for 41.8% of the total variations, including 394 SNVs (59.7%), nine block substitutions (1.36%), 207 InDels (31.36%), and 50 mixed variations (7.58%). The tRNA regions contained 63 variants, accounting for 3.99% of the total variations, including 47 SNVs (74.6%) and 14 InDels (22.2%). The highest number of variants were detected in the IGS regions, while the lowest were found in introns. Among CDSs, accD (183) had the highest number of variations. In introns, rpL16 (18) and ndhA (16) had the most variants. In the IGS regions, ndhD-trnI-CAU (73), and trnL-UAA-trnT-UGU (44) possessed the greatest number of variants.

    Figure 6.  Variant locations within the pea pan-plastome categorized by genic position (Introns, CDS, and IGS).

    Finally, examples of some genes with typical variants were provided to better illustrate the sequence differences between clades (Fig. 7). For example, the present analysis revealed that the ycf1 gene exhibited a high number of variant loci, which included unique single nucleotide variants (SNVs) specific to the P. abyssinicum clade. Additionally, a unique InDel variant belonging to P. abyssinicum was identified. Similar unique SNVs and InDels were also found in other genes, such as matK and rpoC2, distinguishing the P. fulvum clade from others. These unique SNVs and InDels could serve as DNA barcodes to distinguish different maternal lineages of peas.

    Figure 7.  Examples of variant sites.

    The present research combined 145 pea plastomes to construct a pan-plastome of peas. Compared to single plastomic studies, pan-plastome analyses across a species or genus provide a higher-resolution understanding of phylogenetic relationships and domestication history. Most plastomes in plants possess a quadripartite circular structure with two inverted repeat (IR) regions and two single copy regions (LSC and SSC)[2024]. However, the complete loss of one of the IR regions in the pea plastome was observed which is well-known among the inverted repeat-lacking clade (IRLC) species in Fabaceae. The loss of IRs has been documented in detail from other genera such as Erodium (Geraniaceae family)[26,27] and Medicago (Fabaceae family)[28,29]. This phenomenon although not commonly observed, constitutes a significant event in the evolutionary trajectories of certain plant lineages[26]. Such large-scale changes in plastome architecture are likely driven in part by a combination of selective pressures and genetic drift[48]. In the pea pan-plastome, it was also found that, compared to some plants with IR regions, the length of the plastomes was much shorter, and the overall GC content was lower. This phenomenon was due to the loss of one IR with high GC content.

    Repetitive sequences are an important part of the evolution of plastomes and can be used to reconstruct genealogical relationships. Mononucleotide SSRs are consistently abundant in plastomes, with many studies identifying them as the most common type of SSR[4952]. Among these, while C/G-type SSRs may dominate in certain species[53,54], A/T types are more frequently observed in land plants. The present research was consistent with these previous conclusions, showing an A/T proportion exceeding 90% (Fig. 4). Due to their high rates of mutation, SSRs are widely used to study phylogenetic relationships and genetic variation[55,56]. Additionally, like other plants, pea plastome genes have a high frequency of A/Ts in the third codon position. This preference is related to the higher AT content common among most plant plastomes and Fabaceae plastomes in particular with their single IRs[57,58]. The AT-rich regions are often associated with easier unwinding of DNA during transcription and potentially more efficient and accurate translation processes[59]. The preference for A/T in third codon positions may also be influenced by tRNA availability, as the abundance of specific tRNAs that recognize these codons can enhance the efficiency of protein synthesis[60,61]. However, not all organisms exhibit this preference for A/T-ending codons. For instance, many bacteria have GC-rich genomes and thus show a preference for G/C-ending codons[6264]. This variation in codon usage bias reflects the differences in genomic composition and the evolutionary pressures unique to different lineages.

    This study also comprehensively examined the variant loci of the pea pan-plastome. Among these variant sites, some could potentially serve as DNA barcode sites for specific lineages of peas, such as ycf1, rpoC2, and matK. Both ycf1 and matK have been widely used as DNA barcodes in many species[6568], as they are hypervariable. Researchers now have a much deeper understanding of the crucial role plastomes have played in plant evolution[6971]. By generating a comprehensive map of variant sites, future researchers can now more effectively trace differences in plastotypes to physiological and metabolic traits for use in breeding elite cultivars.

    The development of a pan-plastome for peas provides new insights into the maternal domestication history of this important food crop. Based on the phylogenetic analysis in this study, we observed a clear differentiation between wild and cultivated peas, with P. fulvum being the earliest diverging lineage, and was consistent with former research[34]. The ML tree (Fig. 5a) indicated that cultivated peas had undergone at least two independent domestications, namely from the PA and PS groups, which is consistent with former research[34]. However, as the present study added several accessions over the previous study and plastomic data was utilized, several differences were also found[34], such as the resolution of the two groups, referred to as PSeI-a group and PSeI-b group which branched between the PA group and PF group. Previous research based on nuclear data[34] only and with fewer accessions showed that the PA group and PF group were closely related in phylogeny, with no PSeI group appearing between them. One possible explanation is that the PSeI-a and PSeI-b lineages represents the capture and retention of a plastome from a now-extinct lineage while backcrossing to modern cultivars has obscured this signal in the nuclear genomic datasets. However, procedural explanations such as incorrectly identified accessions might have also resulted in such patterns. In either case, the presence of these plastomes in the cultivated pea gene pool should be explored for possible associations with traits such as disease resistance and hybrid incompatibility. This finding underscores the complexity of the domestication process and highlights the role of hybridization and selection in shaping the genetic landscape of cultivated peas. As such, future studies integrating data from the nuclear genome, mitogenome, and plastome will undoubtedly provide deeper insights into the phylogeny and domestication of peas. This pan-plastome research, encompassing a variety of cultivated taxa, will also support the development of elite varieties in the future.

    This study newly assembled 103 complete pea plastomes. These plastomes were combined with 42 published pea plastomes to construct the first pan-plastome of peas. The length of pea plastomes ranged from 120,826 to 122,547 bp, with the GC content varying from 34.74% to 34.87%. The codon usage pattern in the pea pan-plastome displayed a strong bias for A/T in the third codon position. Besides, the codon usage of petB, psbA, rpl16, rps14, and rps18 were shown extremely influenced by natural selection. Three types of SSRs were detected in the pea pan-plastome, including A/T, AT/TA, and AAT/ATT. From phylogenetic analysis, seven well-supported clades were resolved from the pea pan-plastome. The genes ycf1, rpoC2, and matK were found to be suitable for DNA barcoding due to their hypervariability. The pea pan-plastome provides a valuable supportive resource in future breeding and selection research considering the central role chloroplasts play in plant metabolism as well as the association of plastotype to important agronomic traits such as disease resistance and interspecific compatibility.

  • The authors confirm contribution to the paper as follows: study conception and design: Wang J; data collection: Kan J; analysis and interpretation of results: Kan J, Wang J; draft manuscript preparation: Kan J, Wang J, Nie L; project organization and supervision: Tiwari R, Wang M, Tembrock L. All authors reviewed the results and approved the final version of the manuscript.

  • The annotation files of newly assembled pea plastomes were uploaded to the Figshare website (https://figshare.com/, doi: 10.6084/m9.figshare.26390824).

  • This study was funded by the Guangdong Pearl River Talent Program (Grant No. 2021QN02N792) and the Shenzhen Fundamental Research Program (Grant No. JCYJ20220818103212025). This work was also funded by the Science Technology and Innovation Commission of Shenzhen Municipality (Grant No. RCYX20200714114538196) and the Innovation Program of Chinese Academy of Agricultural Sciences. We are also particularly grateful for the services of the High-Performance Computing Cluster in the Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences.

  • The authors declare that they have no conflict of interest.

  • Supplemental Fig. S1 The total ion chromatograms of the QC (A) and PCA scores plot of samples and QC (B).
    Supplemental Fig. S2 Differentiation of different dried lily bulbs in negative mode. A) Venn plot. B) PCA scores plot, indicating discrimination between HD, FD and MD. C) heatmap D) Pearson correlation.
    Supplemental Fig. S3 The peptides markers in HD. The left part was mirror plots and chemical structures, and the right part was the box-plots. A) Val-Val, B) Glu-Leu, B) Gly-Tyr, D) Asp-Phe.
    Supplemental Fig. S4 The free fatty acids markers in FD. The left part was mirror plots and chemical structures, and the right part was the box-plots. A) palmitic acid, B) heptadecanoic acid, C) stearic acid, D) vaccenic acid E) γ-linolenic acid.
  • [1]

    Li W, Wang Y, Wei H, Zhang Y, Guo Z, et al. 2020. Structural characterization of Lanzhou lily (Lilium davidii var. unicolor) polysaccharides and determination of their associated antioxidant activity. Journal of the Science of Food and Agriculture 100:5603−16

    doi: 10.1002/jsfa.10613

    CrossRef   Google Scholar

    [2]

    Tang Y, Liu Y, Luo K, Xu L, Yang P, et al. 2022. Potential applications of Lilium plants in cosmetics: a comprehensive review based on research papers and patents. Antioxidants 11(8):1458

    doi: 10.3390/antiox11081458

    CrossRef   Google Scholar

    [3]

    Polat A, Izli N. 2022. Drying characteristics and quality evaluation of 'Ankara' pear dried by electrohydrodynamic-hot air (EHD) method. Food Control 134:108774

    doi: 10.1016/j.foodcont.2021.108774

    CrossRef   Google Scholar

    [4]

    Zhang X, Xue L, Wu Z, Zhang W, Zhang H, et al. 2023. Insight into the effects of drying methods on Lanzhou lily rehydration. Foods 12(9):1817

    doi: 10.3390/foods12091817

    CrossRef   Google Scholar

    [5]

    Quan H, Cai Y, Lu Y, Shi C, Han X, et al. 2023. Effect of microwave treatments combined with hot-air drying on phytochemical profiles and antioxidant activities in lily bulbs (Lilium lancifolium). Foods 12(12):2344

    doi: 10.3390/foods12122344

    CrossRef   Google Scholar

    [6]

    Zhang B, Quan H, Cai Y, Han X, Kang H, et al. 2023. Comparative study of browning, phenolic profiles, antioxidant and antiproliferative activities in hot air and vacuum drying of lily (Lilium lancifolium Thunb.) bulbs. LWT 184:115015

    doi: 10.1016/j.lwt.2023.115015

    CrossRef   Google Scholar

    [7]

    Wang K, Liao X, Xia J, Xiao C, Deng J, et al. 2023. Metabolomics: A promising technique for uncovering quality-attribute of fresh and processed fruits and vegetables. Trends in Food Science & Technology 142:104213

    doi: 10.1016/j.jpgs.2023.104213

    CrossRef   Google Scholar

    [8]

    Lou W, Mu X, Liu J, Xun M, Hu Y. 2023. Study on the differences of metabolites and their bioactivities of Lithocarpus under different processing methods. Food Bioscience 54:102817

    doi: 10.1016/j.fbio.2023.102817

    CrossRef   Google Scholar

    [9]

    Wang K, Xu Z. 2022. Comparison of freshly squeezed, non-thermally and thermally processed orange juice based on traditional quality characters, untargeted metabolomics, and volatile overview. Food Chemistry 373:131430

    doi: 10.1016/j.foodchem.2021.131430

    CrossRef   Google Scholar

    [10]

    Kong Y, Wang H, Lang L, Dou X, Bai J. 2021. Metabolome-based discrimination analysis of five Lilium bulbs associated with differences in secondary metabolites. Molecules 26(5):1340

    doi: 10.3390/molecules26051340

    CrossRef   Google Scholar

    [11]

    Tang YC, Liu YJ, He GR, Cao YW, Bi MM, et al. 2021. Comprehensive analysis of secondary metabolites in the extracts from different lily bulbs and their antioxidant ability. Antioxidants 10(10):1634

    doi: 10.3390/antiox10101634

    CrossRef   Google Scholar

    [12]

    Chiang N, Ho CT, Munafo JP Jr. 2018. Identification of key aroma compounds in raw and roasted lily bulbs (Bai He). Flavour and Fragrance Journal 33:294−302

    doi: 10.1002/ffj.3446

    CrossRef   Google Scholar

    [13]

    Mi L, Wang K, Gan Z, Lin Y, Wang X, et al. 2024. A comparative metabolomics study on two fresh edible lilies for vegetable: Lilium brownii var. viridulum and Lilium davidii var. unicolor. Food Bioscience 57:103583

    doi: 10.1016/j.fbio.2024.103583

    CrossRef   Google Scholar

    [14]

    Yang S, Mi L, Wang K, Wang X, Wu J, et al. 2023. Comparative metabolomics analysis in the clean label ingredient of NFC spine grape juice processed by mild heating vs high pressure processing. Food Innovation and Advances 2:95−105

    doi: 10.48130/FIA-2023-0011

    CrossRef   Google Scholar

    [15]

    Pang Z, Zhou G, Ewald J, Chang L, Hacariz O, et al. 2022. Using MetaboAnalyst 5.0 for LC-HRMS spectra processing, multi-omics integration and covariate adjustment of global metabolomics data. Nature Protocols 17:1735−61

    doi: 10.1038/s41596-022-00710-w

    CrossRef   Google Scholar

    [16]

    Baygildieva DI, Braun AV, Stavrianidi AN, Rodin IA. 2020. Determination of Eleutheroside B and Eleutheroside E in Extracts from Eleutherococcus senticosus by liquid chromatography/mass spectrometry. Journal of Analytical Chemistry 75:1832−37

    doi: 10.1134/S1061934820140051

    CrossRef   Google Scholar

    [17]

    Tian Y, Zhao Y, Huang J, Zeng H, Zheng B. 2016. Effects of different drying methods on the product quality and volatile compounds of whole shiitake mushrooms. Food Chemistry 197:714−22

    doi: 10.1016/j.foodchem.2015.11.029

    CrossRef   Google Scholar

    [18]

    Gerrard JA. 2006. The Maillard reaction in food: Progress made, challenges ahead-conference report from the Eighth International Symposium on the Maillard reaction. Trends in Food Science & Technology 17:324−30

    doi: 10.1016/j.jpgs.2005.11.011

    CrossRef   Google Scholar

    [19]

    Liu L, Wang Y, Fan D, Mi Y. 2015. Using phenolphthalein as a promising indicator to monitor the vacuum freeze-drying process. Materials Letters 139:245−48

    doi: 10.1016/j.matlet.2014.10.047

    CrossRef   Google Scholar

    [20]

    Mitra J, Shrivastava SL, Rao PS. 2015. Non-enzymatic browning and flavour kinetics of vacuum dried onion slices. International Agrophysics 29:91−100

    doi: 10.1515/intag-2015-0010

    CrossRef   Google Scholar

    [21]

    Wang X, Yang L, Liu J, Wang R, Zhang Q, et al. 2020. Comparison of the biochemical properties and thermal inactivation of polyphenol oxidase from three lily bulb cultivars. Journal of Food Biochemistry 44:e13431

    doi: 10.1111/jfbc.13431

    CrossRef   Google Scholar

    [22]

    Mastali M, Kinnunen P, Dalvand A, Firouz RM, Illikainen M. 2018. Drying shrinkage in alkali-activated binders - A critical review. Construction and Building Materials 190:533−50

    doi: 10.1016/j.conbuildmat.2018.09.125

    CrossRef   Google Scholar

    [23]

    Mahiuddin M, Khan MIH, Kumar C, Rahman MM, Karim MA. 2018. Shrinkage of Food Materials During Drying: Current Status and Challenges. Comprehensive Reviews in Food Science and Food Safety 17(5):1113−26

    doi: 10.1111/1541-4337.12375

    CrossRef   Google Scholar

    [24]

    Mustafa I, Chin NL, Fakurazi S, Palanisamy A. 2019. Comparison of phytochemicals, antioxidant and anti-inflammatory properties of sun-, oven- and freeze-dried ginger extracts. Foods 8(10):456

    doi: 10.3390/foods8100456

    CrossRef   Google Scholar

    [25]

    An NN, Sun WH, Li BZ, Wang Y, Shang N, et al. 2022. Effect of different drying techniques on drying kinetics, nutritional components, antioxidant capacity, physical properties and microstructure of edamame. Food Chemistry 373:131412

    doi: 10.1016/j.foodchem.2021.131412

    CrossRef   Google Scholar

    [26]

    Zhang M, Tang J, Mujumdar AS, Wang S. 2006. Trends in microwave-related drying of fruits and vegetables. Trends in Food Science & Technology 17(10):524−34

    doi: 10.1016/j.jpgs.2006.04.011

    CrossRef   Google Scholar

    [27]

    Bikaki M, Shah R, Müller A, Kuhnert N. 2021. Heat induced hydrolytic cleavage of the peptide bond in dietary peptides and proteins in food processing. Food Chemistry 357:129621

    doi: 10.1016/j.foodchem.2021.129621

    CrossRef   Google Scholar

    [28]

    Wegener S, Kaufmann M, Kroh LW. 2017. Influence of L-pyroglutamic acid on the color formation process of non-enzymatic browning reactions. Food Chemistry 232:450−54

    doi: 10.1016/j.foodchem.2017.04.046

    CrossRef   Google Scholar

    [29]

    Kirimura J, Shimizu A, Kimizuka A, Ninomiya T, Katsuya N. 1969. Contribution of peptides and amino acids to the taste of foods. Journal of Agricultural and Food Chemistry 17(4):689−95

    doi: 10.1021/jf60164a031

    CrossRef   Google Scholar

    [30]

    Bachmanov AA, Beauchamp GK. 2008. Amino acid and carbohydrate preferences in C57BL/6ByJ and 129P3/J mice. Physiology & Behavior 93(1-2):37−43

    doi: 10.1016/j.physbeh.2007.07.016

    CrossRef   Google Scholar

    [31]

    Alim A, Yang C, Song H, Liu Y, Zou T, et al. 2019. The behavior of umami components in thermally treated yeast extract. Food Research International 120:534−43

    doi: 10.1016/j.foodres.2018.11.002

    CrossRef   Google Scholar

    [32]

    Liu JB, Liu MY, He CC, Song HL, Chen F. 2015. Effect of thermal treatment on the flavor generation from Maillard reaction of xylose and chicken peptide. LWT - Food Science and Technology 64(1):316−25

    doi: 10.1016/j.lwt.2015.05.061

    CrossRef   Google Scholar

    [33]

    Delgado T, Pereira JA, Ramalhosa E, Casal S. 2017. Comparison of different drying methods on the chemical and sensory properties of chestnut (Castanea sativa M.) slices. European Food Research and Technology 243:1957−71

    doi: 10.1007/s00217-017-2902-6

    CrossRef   Google Scholar

    [34]

    Tenyang N, Ponka R, Tiencheu B, Djikeng FT, Womeni HM. 2020. Effect of traditional drying methods on proximate composition, fatty acid profile, and oil oxidation of fish species consumed in the far-north of Cameroon. Global Challenges 4(8):2000007

    doi: 10.1002/gch2.202000007

    CrossRef   Google Scholar

    [35]

    Saidi B, Warthesen JJ. 1995. Effect of heat and homogenization on riboflavin photolysis in milk. International Dairy Journal 5(7):635−45

    doi: 10.1016/0958-6946(95)00048-8

    CrossRef   Google Scholar

    [36]

    Okmen ZA, Bayindirli AL. 1999. Effect of microwave processing on water soluble vitamins: kinetic parameters. International Journal of Food Properties 2(3):255−64

    doi: 10.1080/10942919909524609

    CrossRef   Google Scholar

    [37]

    Wang CC, Hsieh PW, Kuo JR, Wang SJ. 2021. Rosmarinic acid, a bioactive phenolic compound, inhibits glutamate release from rat cerebrocortical synaptosomes through GABAA receptor activation. Biomolecules 11(7):1029

    doi: 10.3390/biom11071029

    CrossRef   Google Scholar

    [38]

    Simonetti P, Gardana C, Pietta P. 2001. Plasma levels of caffeic acid and antioxidant status after red wine intake. Journal of Agricultural and Food Chemistry 49(12):5964−68

    doi: 10.1021/jf010546k

    CrossRef   Google Scholar

    [39]

    Petersen M. 1997. Cytochrome P450-dependent hydroxylation in the biosynthesis of rosmarinic acid in Coleus. Phytochemistry 45(6):1165−72

    doi: 10.1016/S0031-9422(97)00135-0

    CrossRef   Google Scholar

    [40]

    Fletcher RS, Slimmon T, McAuley CY, Kott LS. 2005. Heat stress reduces the accumulation of rosmarinic acid and the total antioxidant capacity in spearmint (Mentha spicata L). Journal of the Science of Food and Agriculture 85(14):2429−36

    doi: 10.1002/jsfa.2270

    CrossRef   Google Scholar

    [41]

    Ghafoor K, Al Juhaimi F, Özcan MM, Uslu N, Babiker EE, et al. 2020. Total phenolics, total carotenoids, individual phenolics and antioxidant activity of ginger (Zingiber officinale) rhizome as affected by drying methods. LWT 126:109354

    doi: 10.1016/j.lwt.2020.109354

    CrossRef   Google Scholar

    [42]

    Wang C, Li J, Zhang Y, He Z, Zhang Y, et al. 2022. Effects of electrostatic spray drying on the sensory qualities, aroma profile and microstructural features of instant Pu-erh tea. Food Chemistry 373:131546

    doi: 10.1016/j.foodchem.2021.131546

    CrossRef   Google Scholar

    [43]

    Liu J, Jiao Z, Zhang C, Yang W, Liu H, et al. 2018. Effects of different drying methods on phenolic contents, antioxidant, and tyrosinase inhibitory activity of peach blossoms. Journal of Food Measurement and Characterization 12:2339−48

    doi: 10.1007/s11694-018-9850-0

    CrossRef   Google Scholar

    [44]

    Yang X, Liu T, Qi S, Gu H, Li J, et al. 2022. Tea saponin additive to extract eleutheroside B and E from Eleutherococcus senticosus by ultrasonic mediation and its application in a semi-pilot scale. Ultrasonics Sonochemistry 86:106039

    doi: 10.1016/j.ultsonch.2022.106039

    CrossRef   Google Scholar

    [45]

    Wang R, Chen C, Guo S. 2017. Effects of drying methods on starch crystallinity of gelatinized foxtail millet (α-millet) and its eating quality. Journal of Food Engineering 207:81−89

    doi: 10.1016/j.jfoodeng.2017.03.018

    CrossRef   Google Scholar

    [46]

    Chan CH, Yusoff R, Ngoh GC, Kung FWL. 2011. Microwave-assisted extractions of active ingredients from plants. Journal of Chromatography A 1218(37):6213−25

    doi: 10.1016/j.chroma.2011.07.040

    CrossRef   Google Scholar

    [47]

    Wang Z, Pan H, Xu J, Chang Y, Liu C, et al. 2022. A sustainable and integrated natural surfactant mediated microwave-assisted extraction technique enhances the extraction of phytochemicals from plants. Industrial Crops and Products 184:115043

    doi: 10.1016/j.indcrop.2022.115043

    CrossRef   Google Scholar

    [48]

    Gray N, Lawler NG, Yang R, Morillon AC, Gay MCL, et al. 2021. A simultaneous exploratory and quantitative amino acid and biogenic amine metabolic profiling platform for rapid disease phenotyping via UPLC-QToF-MS. Talanta 223(Part 2):121872

    doi: 10.1016/j.talanta.2020.121872

    CrossRef   Google Scholar

    [49]

    Das PR, Islam MT, Lee SH, Lee MK, Kim JB, et al. 2020. UPLC-DAD-QToF/MS analysis of green tea phenolic metabolites in their free, esterified, glycosylated, and cell wall-bound forms by ultra-sonication, agitation, and conventional extraction techniques. LWT 127:109440

    doi: 10.1016/j.lwt.2020.109440

    CrossRef   Google Scholar

    [50]

    Bączek K, Węglarz Z, Przybyl JL. 2011. Accumulation of biologically active compounds in the rhizomes and roots of eleuthero (Eleutherococcus senticosus/Maxim. et Rupr./Maxim.). Advances in Environmental Biology 5(2):325−28

    Google Scholar

  • Cite this article

    Mi L, Yang S, Wang X, Xu L, Lin Y, et al. 2024. Comparing the appearance and phytochemical characterization of dried lily (L. davidii var. unicolor) bulbs processed by different drying technologies. Food Innovation and Advances 3(3): 212−221 doi: 10.48130/fia-0024-0020
    Mi L, Yang S, Wang X, Xu L, Lin Y, et al. 2024. Comparing the appearance and phytochemical characterization of dried lily (L. davidii var. unicolor) bulbs processed by different drying technologies. Food Innovation and Advances 3(3): 212−221 doi: 10.48130/fia-0024-0020

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Comparing the appearance and phytochemical characterization of dried lily (L. davidii var. unicolor) bulbs processed by different drying technologies

Food Innovation and Advances  3 2024, 3(3): 212−221  |  Cite this article

Abstract: Lily bulbs are valued for their health benefits, and drying is a common method for their preservation. This study employed untargeted metabolomics using UHPLC-QTOF-MS to analyze the phytochemical profiles of lily bulbs dried by hot air (HD), microwave (MD), and vacuum freeze (FD) methods. In terms of appearance, FD samples exhibited minimal browning and wrinkling, while HD bulbs showed the most severe changes. Nineteen potential markers were identified, with HD samples showing higher levels of bitter amino acids, peptides, and N-fructosyl phenylalanine. The markers of FD samples were glutamine, coumarin, and p-coumaric acid. Notably, eleutheroside E was detected in lily bulbs for the first time and confirmed as an MD marker, with levels 1.51-fold and 6.19-fold higher than in FD and HD samples, respectively. MD method shows promise for enriching bioactive compounds in dried lily bulbs.

    • Lilium spp., the perennial plant belonging to the family Liliaceaeas, is a cherished ingredient with the homology of medicine and food. L. davidii var. unicolor is famous for its delightful sweet taste[1]. The bulbs, the main edible portion of lily, are frequently consumed for their health-promoting properties. Lily bulbs have been reported as a rich resource of nutrients containing amino acids, dietary fiber, proteins, and so on. They are rich in bioactive phytochemicals as well, such as polyphenolics, polysaccharides, and steroid alkaloids[2].

      However, fresh lily bulbs are perishable and difficult to supply all year round due to the harvest season restrictions[3]. Drying technologies, including hot air drying (HD), vacuum freeze drying (FD), microwave drying (MD), far infrared drying and so on, have been long utilized as the vital processing technique to dehydrate fresh lily bulbs for long-term preservation. Up to now, the effects of different drying technologies on the characteristics of lily bulbs have been reported from the perspective of physicochemical properties such as texture, viscosity, drying kinetics, rehydration performance[4], specific phytochemicals (regaloside, chlorogenic acid p-coumaric acid, and so on), antioxidant, and antiproliferative activity[5,6]. Zhang et al. studied the influences on the rehydration, spatial structure, and physiochemical properties of lily starch with HD, FD, and MD[4]. Quan et al. explored the color, phytochemicals, antioxidant activities, antiproliferation, and cytotoxicity of dried lily bulbs after MD combined with HD, and the content of regaloside A, regaloside B, regaloside C, regaloside E, chlorogenic acid, and p-coumaric acid was determined by HPLC-DAD[5].

      With the advancement of omics techniques, metabolomic analysis has been applied to study the impact of processing technologies on the phytochemical profiles of foods, especially fruits and vegetables[7]. Lou et al. assessed the variation of chemical composition of Lithocarpus with different processing methods using GC-MS and LC-MS[8]. Wang et al. identified 15 differential markers between freshly squeezed and pasteurized orange juices based on metabolomics using LC-QTOF[9]. To our knowledge, several studies have sprung up to differentiate phytochemicals of lily bulbs from varieties using metabolomic techniques[10,11]. Chiang et al. analyzed the profile of volatile constituents of raw and roasted lily bulbs using GC-MS and found the odorants decreased during the roasting process accompanied by the formation of new odorants[12]. Besides, Zhang et al. also studied the dried lily bulbs from the perspective of volatile compounds and activities processed by HD and FD using GC-MS, identified 110 volatile compounds and the most abundant differential compounds (hexanal, 2-hexenal, and (E)-2-nonenal)[6]. As far as we know, limited studies have investigated the drying processing of lily bulbs using LC-MS-based omics tools.

      This study was conducted to compare the appearance properties and phytochemicals profiles of dried lily bulbs processed by three technologies (HD, FD and MD) using UHPLC-QTOF-MS-based untargeted metabolomics. The principal component analysis (PCA) model was performed to distinguish different methods, subsequently, the markers were annotated and discussed. The selected marker was verified and quantified using ultra-performance liquid chromatography-triple quadrupole mass spectrometry (UPLC-QQQ-MS) with reference standard.

    • Methanol was purchased from Merck KGaA (Darmstadt, Germany) and acetonitrile was sourced from Thermo Fisher Scientific (Massachusetts, USA), the standard of eleutheroside E was procured from Yuanye Bio-Technology Co., Ltd (Shanghai, China), and formic acid was purchased from DiKMA Technologies (Beijing, China). Distilled water was purchased from Watsons (Guangzhou, China).

    • The triennial lily bulbs (L. davidii var. unicolor), derived from the same local orchard in Qilihe District, Lanzhou City, Gansu Province, were harvested in October 2021 and selected for the drying process. All samples were preserved in a 4 °C chamber with a relatively humidity of 65%, and processed within 5 d. The parameters of the drying procedure were determined based on the results of a preliminary experiment (data not shown). The 20 g lily bulbs were weighed and spread on a glass petri dish in a single layer for drying by HD, MD, and FD. During HD, the samples were placed in a 60 °C electric thermal dryer and dried for approximately 22 h. For MD, samples were put into a microwave oven (MO-2270M1, Haier Microwave Products Co., Ltd, Qingdao, China) operated for 10 min at a microwave power density of 20 W/g. The FD group was carried out in a vacuum drying oven (LYO-3, Beijing Boyikang experimental instrument Co., Ltd, Beijing, China). After pre-freezing treatment, the samples were dried in 12−14 Pa at −50 °C for 12 h. The endpoint of processing was determined by the moisture contents of final products (below 12%) according to group standard for dried bulbs of L. davidii var. unicolor (T/GSWS 002—2022). Each drying technology was carried out in six replicates.

    • Color measurements were performed using a high-quality colorimeter (3nh NR60CP, Shenzhen 3NH Technology Co., Ltd., Shenzhen, China), and the CIE color parameters including L*, a*, and b* were recorded. The difference of L*, a*, and b* between dried and fresh samples was recorded as ΔL*, Δa*, and Δb*. The color difference (ΔE) compared with fresh samples was calculated using Eqn (1)[9]. Meanwhile, the appearance and color of both dried and fresh samples were documented through photographs.

      ΔE=(ΔL)2+(Δa)2+(Δb)2 (1)
    • Dried lily bulbs were frozen in liquid nitrogen and ground into powder. Referring to the previous study with some modifications[13], the 200 mg sample was placed in a 1.5 mL centrifuge tube. Then, 600 μL cold methanol with 0.125% formic acid was added, followed by vertexing for 15 s, and the samples were ultrasound-treated at 20 °C for 15 min, subsequently centrifuged at 4 °C and 12,000 r/min for 10 min. The supernatant was filtered through a 0.22 μm filter before analysis. The quality control (QC) sample comprised 5 μL of every individual sample.

    • The acquisition was performed using a UHPLC system and Triple TOF 6600 mass spectrometry equipment (AB-SCIEX, Redwood City, CA, USA) according to a previous study[14]. Preliminary separation was operated by the reversed-phase chromatography Acquity UPLC HSS T3 (1.8 μm, 2.1 mm × 100 mm, Waters, MA, USA) with a flow rate of 0.4 mL/min and injection volume of 2 μL. The autosampler was kept at 4 °C, and the column was kept at 40 °C. Mobile phases comprised of 0.2% formic acid aqueous solution (A) and acetonitrile (B). The solvent gradient samples were eluted was: 0−11.50 min, 5%-30% B; 11.50−11.51 min, 30%−100% B; 11.51−15.00 min, 100% B; 15.00−15.01 min, 100%−5% B; and 15.01−18.00 min, 5% B.

      The MS data was captured in both positive and negative ion modes using the information-dependent acquisition (IDA) mode. The scan m/z range was set as 50−1,000 Da. The cycle time of IDA-MS was 545 ms, comprising 50 ms of a TOF MS scan and 30 ms of product ion scans. The collision energy (CE) of MS was 10 eV/−10 eV. The CE and collision energy spread (CES) of MS/MS was 35 eV/−35 eV, and 15 eV, respectively. QC was used to monitor the reproducibility of each analytical run.

    • The converted ABF files were imported to MS-DIAL for noise filtration, peak detection, alignment, and identification. In peak detection, the minimum peak height was 1,000 amplitudes, and the tolerance for retention time and MS1 were 0.1 min and 0.015 Da. During alignment, the tolerance for MS1 and MS2 of data collection were set to 0.01 and 0.025 Da, respectively. The accurate mass MS1 and MS2 tolerance of identification were set to 0.01 and 0.05 Da. Features were removed based on the ratio of maximum in the samples and mean in the blank samples at least five times. According to the exported list of peak area, the features with relative standard deviation (RSD) of QC greater than 30% and detection rate (DR) lower than 80% were removed. Subsequently, the features were selected based on the quality of MS2, average area, and DR, and those with missing MS2 data, and DR lower than 80% in each drying technology were eliminated. Then, the fold change (FC) and the student's t-test were performed using Excel 2019 (Microsoft Corporation, USA).

      Based on the retention time, accurate mass, isotope ratios, and the spectrum of MS2, the phytochemicals were annotated by matching with online databases. PCA and correlation heatmaps were conducted using the online platform MetaboAnalyst 5.0[15]. The compounds with an absolute value of FC greater than 1.5 and a p-value (t-test) lower than 0.05 were identified as potential differential markers.

    • The extraction of eleutheroside E was adapted from previous published study slightly[16]. The 200 mg dried lily bulb sample was extracted with 1 mL 50% ethanol solution, subsequently ultrasonic extraction was carried out at 40 °C for 30 min, centrifugation at 4 °C, and 10,000 r/min for 15 min. The supernatant was collected and filtered through a 0.22 μm syringe filter before analysis.

      The quantitative analysis of eleutheroside E was conducted using UPLC-QQQ-MS and the external standard method. The UPLC condition was consistent with untargeted metabolomics analysis (2.4.2). The condition of QQQ-MS was optimized using reference standards. Eight different concentration (1, 2, 5, 10, 20, 50, 100, and 200 μg/L) standards of each analyte were run separately. Multiple reaction monitoring (MRM) mode and operated in negative mode (m/z 787.2, with subsequent determination of daughter ions at m/z 1579.3 and 741.3). The optimized CE was −22/−16 V. The optimized DP was −70/−73 V. The injection volume was 2 μL.

    • Appearance is a critical quality parameter influencing consumer acceptance and market value of dried products. Fig. 1 shows the appearance of fresh and dried lily bulbs with three different drying technologies. The FD samples were white and had scarcely any shrinkage in volume compared to fresh samples. For HD and MD samples, the appearance presented varying degrees of brownish-yellow coloration and shrinkage. The color attributes are evaluated in terms of the value of L*, a*, b*, and ΔE, the highest L* and the lowest ΔE are considered to be the benchmarks for the color quality of food[17]. As shown in Table 1, in agreement with the above morphology results, an increase of 9.67% in L* was observed in FD samples, while decreases of 35.95% and 15.09% occurred in HD and MD samples compared to fresh ones. Meanwhile, the highest ΔE was observed in HD samples (26.79 ± 1.75), which was significantly higher than that of MD (14.00 ± 1.35) and FD samples (7.39 ± 1.05), indicating that HD samples bore the worst deterioration in quality.

      Figure 1. 

      The appearance of dried bulbs processed by different drying methods.

      Table 1.  The color index of dried bulbs processed by different drying methods.

      Drying
      methods
      ΔL* Δa* Δb* ΔE
      HD −23.60 ± 2.37c 4.06 ± 0.77a 11.69 ± 2.15a 26.79 ± 1.75a
      FD 6.22 ± 1.57a 0.48 ± 0.10c 3.75 ± 0.73b 7.39 ± 1.05c
      MD −9.58 ± 1.92b 2.71 ± 0.32b 9.55 ± 1.71a 14.00 ± 1.35b
      ΔL*, Δa*, and Δb* represent the difference between dried bulbs and fresh samples. Values followed by lowercase letters indicate the significant difference at the 0.05 level in the same column.

      The browning during drying is mainly related to enzymatic and Maillard reaction[18]. In addition, the oxygen-free environment inhibited the occurrence of enzymatic browning to maintain the appearance of FD samples[19]. Additionally, the threshold activation energy of non-enzymatic browning kinetics was higher than that of HD, reducing the Maillard reaction[20]. Higher temperature aggravated the occurrence of Maillard reaction resulting in non-enzymatic browning in both MD and HD samples. Besides, polyphenol oxidase (PPO) and peroxidase (POD) in lily bulbs can maintain activity at the initial stage[21], and promote the enzymatic browning of polyphenol substrates in fresh bulbs in HD samples.

      The shrinkage after drying was mainly caused by shrinkage stress[22] and internal thermal stress[23]. During the FD process, due to the principle of ice crystal sublimation and low temperature, the shrinkage stress and thermal stress do not generate. In the HD process, the sample's surface temperature is greater than the internal temperature due to uneven heat conduction, leading to the rapid diffusion of external water and difficulty in the escape of internal water[23,24]. Therefore, the shrinkage stress and internal thermal stress easily result in the shrinkage phenomenon. While in the MD group, polar molecules, such as water molecules, move with the change of external electromagnetic field, and generate heat energy by friction and collision with each other at the same speed as the microwave frequency, so the inside of the material heats up rapidly in a short time[25]. Too fast mass transport by microwave may cause a 'puffing' influence[26], thus exhibiting little expansion, and the shrinkage was less than HD samples due to shorter time.

    • The total ion chromatograms of the QC and PCA score plot of samples showed that the untargeted data acquisition was stable enough for further analysis (Supplemental Fig. S1). The UHPLC-QTOF-MS data contained 3383 features in positive mode and 2158 features in negative mode. As illustrated in Fig. 2a and Supplemental Fig. S2a, in positive mode, there were 2,311 features detected in HD, 1,772 features in MD, and 1,611 features in FD. In negative mode, there were 2,060 features detected in HD, 1,788 features in MD, and 1,726 features in FD. Compared with HD, the detected features of MD decreased by 25.5% and 13.2%, and the detected features of FD decreased by 30.3% and 16.2%, in positive and negative modes respectively, indicating that HD may contain more components, possibly resulting from the destruction of components and/or the creation of intermediates. Among them, 1,718 features were shared between HD and MD, 1,569 features were shared between HD and FD, and 1,455 features were shared between MD and FD. The influence of different drying technologies on compounds was explored by comparing them in pairs.

      Figure 2. 

      Differentiation of different dried lily bulbs in positive mode. (a) Venn plot. (b) PCA scores plot. (c) heatmap. (d) Pearson correlation. (e), (f) Volcano plot of features in dried bulbs processed by different drying methods: HD & MD, FD & HD, FD & MD.

      In the PCA scores plot, the PC1 and PC2 accounted for 42.8% and 16.1% of the total variance in positive mode, and 38.4% and 13.5% in negative mode (Fig. 2b & Supplemental Fig. S2b). The sum of the variations explained by PC1 and PC2 was more than 50%, indicating the significant variations. The heatmap illustrated the similarity among replicate samples and differences between different drying methods (Fig. 2c & Supplemental Fig. S2c). Similarly, Pearson correlation analysis showed good uniformity among samples within each group (Fig. 2d & Supplemental Fig. S2d).

    • After the feature screening and multivariate analysis, 690 features were determined as a differential between HD and FD, 714 features between HD and MD, and 227 features between FD and MD (Fig. 2eg). Due to the complexity of the spectrum and incomplete phytochemical database, 127 compounds were potentially identified between HD and FD, 89 compounds between HD and MD, and 67 compounds between FD and MD. Special attention was paid to the features whose MS2 spectra matched well with the databases, i.e., the total score and dot product score both were higher than 80. Compounds that were higher in each group compared with others were considered as markers, the detailed information of markers are listed in Table 2. In total, 19 potential markers were identified. The markers of HD included seven amino acids and peptides, two phenolic acids and one natural vitamin. Eight compounds were considered as markers of FD, which included one amino acid, one coumarin, one phenolic acid, and five kinds of free fatty acids. A triterpenoid saponin, eleutheroside E was annotated as the marker of MD.

      Table 2.  Tentative markers in dried lily bulbs processed by different methods.

      No Compounds Classification m/z Ionization model Retention
      time (min)
      Formula Error
      (ppm)
      HD 1 Tryptophan Amino acid 205.0970 [M+H]+ 4.187 C11H12N2O2 −1.511
      2 Phenylalanine Amino acid 166.0877 [M+H]+ 2.769 C9H11NO2 8.550
      3 Val-val Dipeptide 217.1554 [M+NH4]+ 2.461 C10H20N2O3 −0.092
      4 Glu-Leu Dipeptide 259.1283 [M-H] 3.375 C11H20N2O5 −2.933
      5 Gly-Tyr Dipeptide 239.1032 [M+H]+ 2.313 C11H14N2O4 −3.179
      6 Asp-Phe Dipeptide 281.1137 [M+H]+ 4.294 C13H16N2O5 −4.802
      7 N−Fructosyl phenylalanine Other 328.1412 [M+H]+ 2.692 C15H21NO7 7.344
      8 Rosmarinic acid Hydroxycinnamic acid 163.0411 [M+H-C9H10O5]+ 8.453 C18H16O8 8.280
      9 Caffeic acid Hydroxycinnamic acid 181.0450 [M+H] 4.599 C9H8O4 4.748
      10 (-)-Riboflavin Vitamin 163.0411 [M+H]+ 6.514 C17H20N4O6 −1.538
      FD 11 Glutamine Amino acid 147.0757 [M+H]+ 7.208 C5H10N2O3 −5.031
      12 Coumarin Coumarin 147.0443 [M+H]+ 10.316 C9H6O2 1.700
      13 p−Coumaric acid Hydroxycinnamic acid 147.0459 [M+H]+ 8.393 C9H8O3 10.677
      14 Palmitic acid Free fatty acid 255.2360 [M-H] 14.792 C16H32O2 11.558
      15 Heptadecanoic acid Free fatty acid 269.2468 [M-H] 15.208 C17H32O2 −5.868
      16 γ−Linolenic acid Free fatty acid 277.2164 [M-H] 13.868 C18H30O2 −3.319
      17 Vaccenic acid Free fatty acid 281.2472 [M-H] 14.873 C18H34O2 −5.653
      18 Stearic acid Free fatty acid 283.2637 [M-H] 15.754 C18H36O2 −2.048
      MD 19 Eleutheroside E Triterpenoid saponin 787.2607 [M+FA-H] 8.024 C34H46O18 −7.520
    • In HD, two amino acids and four dipeptides were found in higher concentrations. Tryptophan and phenylalanine in HD were 10.12-fold, and 2.79-fold higher compared to FD, and 6.37-fold, and 2.39-fold higher compared to MD, respectively (Fig. 3a, b). In addition, a couple of dipeptides, Val-Val, Glu-Leu, Gly-Tyr, and Asp-Phe, were more abundant in HD samples (Supplemental Fig. S3). The content of Val-Val, Glu-Leu, Gly-Tyr, and Asp-Phe in HD was 10.57-fold, 4.24-fold, 4.32-fold, 4.06-fold compared to FD, and 47.50-fold, 5.86-fold, 4.27-fold, 19.67-fold compared to MD, respectively. Notably, glutamine was higher in FD, being 2.18-fold and 2.13-fold higher compared to HD and MD, respectively (Fig. 3c).

      Figure 3. 

      The annotated markers among different drying methods. The left part are mirror plots and chemical structures, and the right part are box-plots. (a) Tryptophan, (b) phenylalanine, (c) glutamine (d) N-fructosyl-phenylalanine, (e) riboflavin, (f) rosmarinic acid, (g) caffeic acid, (h) coumarin, (i) p-coumaric acid, and (j) eleutheroside E.

      During the drying process, the structure and stability of proteins in lily bulbs could be influenced by the relatively higher temperature[27], leading to the degradation of proteins as well as the production of amino acids and peptides in HD and MD, so higher contents of tyrosine, tryptophan, phenylalanine, Val-Val, Glu-Leu, Gly-Tyr, and Asp-Phe were observed in both groups compared to FD. In our research, the higher content of L-pyroglutamic acid was observed in HD and MD with 15.34-fold and 15.19-fold compared to FD, likely due to rapid cyclization of glutamine to L-pyroglutamic during the thermal treatment. Besides, the presence of L-pyroglutamic led to the increment of low molecular colored compounds involved in the Maillard reaction[28]. Unexpectedly, the intermediate product of the Maillard reaction, N-fructosyl phenylalanine, was identified with its content being 409.15-fold and 14.63-fold higher in HD compared to FD and MD (Fig. 3d). It indicated the intensified non-enzymatic browning in HD, which was accordance with the result of appearance. The bulbs of L. davidii var. unicolor have plentiful endogenous sugar including sucrose, glucose and fructose[13], and sucrose could be hydrolyzed into glucose, and fructose subsequently, the increment in substrate concentrations and temperature can intensify the Maillard reaction. The by-product, N-fructosyl phenylalanine, was likely derived from fructose and phenylalanine. Notably, the abundance of phenylalanine was still higher in HD, suggesting that the proteins in lily bulbs did degrade.

      It is well-known that free amino acids in natural food are vital for sensory, and the flavor of amino acids is determined by the hydrophobicity of side chain R groups to some extent[29]. The amino acids that were more abundant in HD were known as bitter amino acids, and may negatively affect the taste of dried lily bulbs. Conversely, glutamine is perceived to have umami and desirable taste due to its hydrophilic property[30], the higher content of glutamine in FD may improve the taste of dried lily bulbs. Similarly, the taste of peptides is closely associated with their structure, Val-Val was also found to impart bitter taste and existed in 100 °C samples of thermally treated yeast extract[31]. As opposed to this, the acidic amino acid residues in peptides might be related to its umami taste, Glu-Leu can exhibit kokumi and umami taste[32]. The specific properties of Gly-Tyr and Asp-Phe are yet to be explored.

    • The fluctuation in fatty acids among different drying methods was observed. Saturation fatty acids (SFA), such as palmitic acids, heptadecanoic acid, stearic acid and monounsaturated fatty acid (MUFA) vaccenic acid, and polyunsaturated fatty acid γ-linolenic acid were found in significantly higher concentrations in FD samples (Supplemental Fig. S4). γ-Linolenic acid, a principal PUFA, is known to be affected by drying techniques[33], which is consistent with our findings. High temperature during HD facilitates the destruction of double bonds in MUFA and PUFA, leading to the oxidation of lipids[34]. The oxidation and degradation of free fatty acids may be partially mitigated by the cold and vacuum conditions of FD, showing its superiority in preserving free fatty acids.

    • The content of riboflavin was higher in HD with 5.89-fold compared to FD and 11.46-fold compared to MD (Fig. 3e). It is well-known that riboflavin is susceptible to light rather than heat[35]. The shading treatment was not conducted and thus the light-sensitive compounds were not especially protected in the present experiment. During the process of drying, HD retained more riboflavin due to the darker environment in the lab oven, on the other hand, the radiation between radio waves and ultraviolet wavelengths produced by microwave was responsible for the degradation of riboflavin[36]. The difference in riboflavin content came from the condition of an experiment rather than processing factors, suggesting that FD, conducted in a dark operation, might better preserve light-sensitive compounds.

    • Four polyphenol compounds were identified as markers of different drying methods, including rosmarinic acid, caffeic acid and p-coumaric acid, as well as coumarin. Coumarin without hydroxy is usually classified into polyphenol compounds due to their similar characteristics. Because of their tolerance to heat, rosmarinic acid, and caffeic acid were more abundant in HD compared to FD and to MD (Fig. 3f, g). The content of thermosensitive coumarin and p-coumaric acid were higher in FD. Compared to HD, the contents of coumarin and p-coumaric acid were 3.05-fold and 5.01-fold higher in FD, and their contents were 2.77-fold and 1.52-fold higher in MD, respectively (Fig. 3h, i).

      Rosmarinic acid is a plant-derived high-temperature resistance polyphenolic compound with neuroprotective effects[37]. Caffeic acid has potential anti-oxidant and anti-neoplastic activities, and is distributed in plants[38]. Rosmarinic acid is synthesized enzymatically by the phenylalanine and tyrosine[39]. Caffeic acid, dihydroxyphenyllactic acid, and caffeic ester rosmarinic acid are important intermediate products in the biosynthetic process of rosmarinic acid, and the key enzyme rosmarinic acid synthase (RAS) is heat-stable at 180 °C[40]. The higher substrates and suitable conditions of enzyme led to the accumulation of rosmarinic acid and caffeic acid in HD samples[37]. Quan et al. found the content of p-coumaric acid in 100 W/300 W of MD for 2 min was lower than in fresh samples[5].

      During the drying process, the differences in phenolic compound content could be attributed to process parameters, thermal procedures, and so on[41]. The sealed vacuum chamber of FD provided an oxygen-free environment, the moisture was removed from the lily bulbs under low temperature[42], which may restrain the oxidation and thermal degradation of polyphenols during the FD process. Additionally, the ice crystals formed during dehydration within the plant tissues may foster the extraction of polyphenols due to the collapse of cell structure[43].

    • A triterpenoid saponin, eleutheroside E, was identified as the marker of MD, whose peak area was 2.13-fold compared to FD and 29.31-fold compared to HD (Fig. 3j). Researchers have noted that eleutheroside E possesses numerous pharmacological effects including anti-fatigue, and improvement in peripheral blood circulation and memory[44]. During the microwave drying process, polar molecules such as water in the bulbs of L. davidii var. unicolor release energy by oscillating under the action of an electromagnetic field. Simultaneously, intense heat may produce a sudden high pressure inside the plant matrix, leading to its destruction[43]. The continuous vapor flow might form more 'channels' in the more porous structure of a cell[45]. The morphology of MD samples changed and local swelling was observed, indicating the cell structure was changed under microwave. In the case of the plant matrix being broken down by microwave radiation, bioactive compounds will be released[46], which might lead to the elevation of eleutheroside E in MD samples. Ice crystal and vacuum conditions contributed to the highly porous structure of cells during the process of FD[4], the low temperature also protected the structure of eleutheroside E. The threats of oxidation and thermal degradation of eleutheroside E in HD were elevated due to higher temperature over a long period. It has been reported that almost no pores and channels were observed in dried lily bulbs[4], thus the mass transfer of eleutheroside E was affected. Unlike HD, the shorter drying time could reduce eleutheroside E from thermal degradation in MD.

      In summary, as shown in Fig. 4, non-thermal processing technology, like FD, could provide dried lily bulbs with a quality closer to that of fresh bulbs compared to HD and MD. From FD to HD, the compounds of dried lily bulbs degraded, producing by-products and decomposition products, leading to an increase of components from non-thermal to thermal technology. The bitter amino acids, bitter peptides, and the Maillard intermediate were higher in the HD group, which may be influenced by protein degradation, aggravated Maillard reaction, and increased related reaction products resulting from the thermal process. The markers of the FD group were characterized by glutamine, coumarin, p-coumaric acid and unsaturated fatty acids, proving that vacuum and low temperature effectively inhibited enzymatic reactions, and ice crystal was beneficial to releasing intracellular components. The marker of MD group was eleutheroside E, which benefited from shorter processing time, intense heat, and sudden high pressure inside the matrix due to the electromagnetic field. The variation of phytochemicals among the three drying methods confirmed the alteration in quality and influenced the appearance of dried lily bulbs.

      Figure 4. 

      The tentative mechanism of markers in different drying methods. Note: The number of compounds and ΔE of HD were considered as 1, and the values of FD and MD were compared with HD.

    • Given that eleutheroside E has not been reported in lily bulbs previously, verification and quantitative analysis were conducted using the reference standards. The extraction ion chromatogram of eleutheroside E at the qualitative ion pair 787.2/579.3 was shown in Fig. 5a, confirming the presence of eleutheroside E in the bulbs of L. davidii var. unicolor. It was the first time that eleutheroside E was confirmed in lily bulbs. In Fig. 5b, eleutheroside E had the highest content in MD samples (160.54 ± 25.55 μg/100g DW), followed by FD samples (106.13 ± 8.07 μg/100g DW), and the lowest content in HD samples (25.95 ± 2.47 μg/100g DW). The content of eleutheroside E in HD was significantly lower than fresh samples (63.48 ± 3.52 μg/100g DW) due to the heat-induced degradation. The content of eleutheroside E in MD was 1.51-fold compared to FD and 6.19-fold compared to HD. However, the relative quantitative analysis of eleutheroside E based on the untargeted metabolomics show that the FC of MD compared to FD, and HD was 2.13-fold and 29.31-fold. The discrepancy between absolute and relative quantification might be associated with the extraction solvent, temperature, and other factors. Moderate concentration (40%−50%) ethanol is usually used as the solvent for eleutheroside E[47], and the reference standards were usually dissolved in water, thus the 50% ethanol was a more suitable solvent for the extraction of eleutheroside E compared to 0.125% formic acid methanol. Additionally, the peak area of eleutheroside E in HD was only 4639, far lower than that in FD and MD, potentially affected by noise from the complex matrix, influencing the relative quantitative result. And QQQ-MS is considered the 'gold standard' for quantitative measurement due to its high sensitivity and specificity[48]. Thereby, it was necessary to conduct the targeted extraction and verification test to overcome the limitation of relative quantitation and ensure accuracy.

      Figure 5. 

      Extracted ion chromatogram of (a) standard and samples and (b) the content of eleutheroside E in samples. Note: The precursor ion and the product ion of eleutheroside E were 787.2/579.3 Da.

      In addition, the content of eleutheroside E in MD and FD was 2.53-fold and 1.67-fold compared to fresh lily bulbs, it was speculated that MD and FD did not merely promote the release of eleutheroside E with free state from inside the cell. It has been reported that secondary metabolites normally occur in plants in the free or cell wall-bound form[49]. It was speculated that MD and FD not only promoted the release of free-state eleutheroside E from inside the cell but also facilitated the mass transfer of cell wall-bound compounds. However, further investigations on the distribution of eleutheroside E in plants are required. Moreover, the content of eleutheroside E in MD samples was significantly higher than FD, which might be influenced by the additional electrical effects, such as magnetic effect of microwave, thus promoting the release of eleutheroside E.

      Eleutheroside E is a natural product abundant in Eleutherococcus species, and the rhizome and root of E. Senticosus was reported to possess higher content ranging from 35.67 to 81.29 mg/100g DW along ages of plants[50]. In our study, eleutheroside E was found in lily bulbs at low abundance, making it a less suitable source for eleutheroside E compared to E. Senticosus. However, it was necessary to investigate the distribution of eleutheroside E in other organs of lily. Considering the renewable and preciousness of perennial medical plants, the extraction of the main active constituents have been studied over the past decades. Wang et al. utilized microwave-assisted extraction technique to enhance the yield of eleutheroside E from naturally dried E. Senticosus stem, acquired approximately 165.84 mg/100g DW of eleutheroside E which was higher than Bączek et al.[47,50]. Therefore, it was encouraging that the microwave drying method might have the potential to enrich bioactive compounds before extraction, as microwave was beneficial for the extraction of eleutheroside E.

    • In conclusion, the present study provides a comprehensive analysis of the effects of different drying technologies on dried lily bulbs, from external appearance to internal phytochemical profiles. The FD method resulted in the best external appearance, with minimal browning and wrinkling, while the HD method led to the most significant browning and wrinkling. Through untargeted metabolomics, 19 phytochemical markers were potentially identified to differentiate the drying methods. The HD method increased the levels of bitter amino acids, peptides, and Maillard intermediates, likely due to protein degradation and an intensified Maillard reaction. In contrast, the FD method preserved glutamine, coumarin, p-coumaric acid, and unsaturated fatty acids, attributed to the low-temperature, oxygen-free conditions, and the assistance of ice crystals. Notably, the MD method emerged as a promising technique for enriching bioactive compounds, particularly eleutheroside E, which was found in lily bulbs for the first time in our study. The MD method achieved the highest content of eleutheroside E, suggesting that the disruption of cell structure during drying and the non-thermal effects of microwaves might enhance the release of this bioactive compound. Future research should further investigate the mechanisms underlying the release of bioactive compounds during MD. The present study contributes valuable insights into the impact of drying technologies on the quality of dried lily bulbs and paves the way for the development of processing techniques that preserve and enhance their nutritional and medicinal properties.

    • The authors confirm contribution to the paper as follows: study conception and design: Mi L, Xu Z, Yang SM; experimental processing: Mi L, Wang X, Lin Y; data collection and validation: Mi L, Yang SN; analysis and interpretation of results: Mi L; draft manuscript preparation: Mi L, Yang SN, language editing, manuscript revision: Xu Z, Xu L. All authors reviewed the results and approved the final version of the manuscript.

    • The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

      • This work was supported by the National Natural Science Foundation of China (NSFC) (Grant No. 3222 2067), and the project of Department of Agriculture and Rural Affairs of Gansu Province (Grant No. SDWJ2021-03).

      • The authors declare that they have no conflict of interest.

      • Supplemental Fig. S1 The total ion chromatograms of the QC (A) and PCA scores plot of samples and QC (B).
      • Supplemental Fig. S2 Differentiation of different dried lily bulbs in negative mode. A) Venn plot. B) PCA scores plot, indicating discrimination between HD, FD and MD. C) heatmap D) Pearson correlation.
      • Supplemental Fig. S3 The peptides markers in HD. The left part was mirror plots and chemical structures, and the right part was the box-plots. A) Val-Val, B) Glu-Leu, B) Gly-Tyr, D) Asp-Phe.
      • Supplemental Fig. S4 The free fatty acids markers in FD. The left part was mirror plots and chemical structures, and the right part was the box-plots. A) palmitic acid, B) heptadecanoic acid, C) stearic acid, D) vaccenic acid E) γ-linolenic acid.
      • Copyright: © 2024 by the author(s). Published by Maximum Academic Press on behalf of China Agricultural University, Zhejiang University and Shenyang Agricultural University. This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.
    Figure (5)  Table (2) References (50)
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    Mi L, Yang S, Wang X, Xu L, Lin Y, et al. 2024. Comparing the appearance and phytochemical characterization of dried lily (L. davidii var. unicolor) bulbs processed by different drying technologies. Food Innovation and Advances 3(3): 212−221 doi: 10.48130/fia-0024-0020
    Mi L, Yang S, Wang X, Xu L, Lin Y, et al. 2024. Comparing the appearance and phytochemical characterization of dried lily (L. davidii var. unicolor) bulbs processed by different drying technologies. Food Innovation and Advances 3(3): 212−221 doi: 10.48130/fia-0024-0020

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