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Comparative evaluation of the impact of processing methods in determining the levels of health promoting chemical constituents and quality of green tea

  • # Authors contributed equally: Biplab Adhikary, Bishwapran Kashyap

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  • The first step of green tea manufacture involves enzyme deactivation by heat application. The present study investigated the effects of various fixing and processing methods viz. steam-roasting (S-6), pan-firing (P-8), blanching (B-2), and CTC cuts after steam-roasting (S-CTC), on the bio-chemical profiles and organoleptic quality of green teas processed differently into orthodox and CTC types, from region-specific tea cultivars, suitable for green tea production under agroclimatic condition of Dooars, West Bengal, India. Differences in fixing method and processing style showed notable variation (p ≤ 0.05) in the chemical quality indicators of green tea viz. Total catechin, polyphenol, flavonoid, and water extract content among the differently processed green teas. The most significant finding of the study revealed that when B-2 is employed for deactivation, it resulted in a substantial reduction (47%−52%) of caffeine levels without affecting the catechins content and antioxidant potential of green tea samples when compared to S-6 and P-8 methods. Interestingly, our results demonstrated significantly higher water extract values (42.19% dry weight) in green CTC teas and lower values in B-2 green tea samples (33.67%), as compared to S-8 and P-8 green teas, which received better taster ratings (≥ 7). These findings have highlighted the role of processing method and the impact of fixing technique in determining the contents of health-promoting attributes and taste quality of green teas, thus providing diverse choices to tea producers and consumers to opt for specific green tea products and expediting the need to further explore its commercial application in the nutraceutical and pharmaceutical industry (Supplemental Fig. S1).
  • As a major staple crop, today maize accounts for approximately 40% of total worldwide cereal production (http://faostat.fao.org/). Since its domestication ~9,000 years ago from a subgroup of teosinte (Zea mays ssp. parviglumis) in the tropical lowlands of southwest Mexico[1], its cultivating area has greatly expanded, covering most of the world[2]. Human's breeding and utilization of maize have gone through several stages, from landraces, open-pollinated varieties (OPVs), double-cross hybrids (1930s-1950s) and since the middle 1950s, single-cross hybrids. Nowadays, global maize production is mostly provided by single-cross hybrids, which exhibit higher-yielding and better stress tolerance than OPVs and double-cross hybrids[3].

    Besides its agronomic importance, maize has also been used as a model plant species for genetic studies due to its out-crossing habit, large quantities of seeds produced and the availability of diverse germplasm. The abundant mutants of maize facilitated the development of the first genetic and cytogenetic maps of plants, and made it an ideal plant species to identify regulators of developmental processes[46]. Although initially lagging behind other model plant species (such as Arabidopsis and rice) in multi-omics research, the recent rapid development in sequencing and transformation technologies, and various new tools (such as CRISPR technologies, double haploids etc.) are repositioning maize research at the frontiers of plant research, and surely, it will continue to reveal fundamental insights into plant biology, as well as to accelerate molecular breeding for this vitally important crop[7, 8].

    During domestication from teosinte to maize, a number of distinguishing morphological and physiological changes occurred, including increased apical dominance, reduced glumes, suppression of ear prolificacy, increase in kernel row number, loss of seed shattering, nutritional changes etc.[9] (Fig. 1). At the genomic level, genome-wide genetic diversity was reduced due to a population bottleneck effect, accompanied by directional selection at specific genomic regions underlying agronomically important traits. Over a century ago, Beadle initially proposed that four or five genes or blocks of genes might be responsible for much of the phenotypic changes between maize and teosinte[10,11]. Later studies by Doebley et al. used teosinte–maize F2 populations to dissect several quantitative trait loci (QTL) to the responsible genes (such as tb1 and tga1)[12,13]. On the other hand, based on analysis of single-nucleotide polymorphisms (SNPs) in 774 genes, Wright et al.[14] estimated that 2%−4% of maize genes (~800−1,700 genes genome-wide) were selected during maize domestication and subsequent improvement. Taking advantage of the next-generation sequencing (NGS) technologies, Hufford et al.[15] conducted resequencing analysis of a set of wild relatives, landraces and improved maize varieties, and identified ~500 selective genomic regions during maize domestication. In a recent study, Xu et al.[16] conducted a genome-wide survey of 982 maize inbred lines and 190 teosinte accession. They identified 394 domestication sweeps and 360 adaptation sweeps. Collectively, these studies suggest that maize domestication likely involved hundreds of genomic regions. Nevertheless, much fewer domestication genes have been functionally studied so far.

    Figure 1.  Main traits of maize involved in domestication and improvement.

    During maize domestication, a most profound morphological change is an increase in apical dominance, transforming a multi-branched plant architecture in teosinte to a single stalked plant (terminated by a tassel) in maize. The tillers and long branches of teosinte are terminated by tassels and bear many small ears. Similarly, the single maize stalk bears few ears and is terminated by a tassel[9,12,17]. A series of landmark studies by Doebley et al. elegantly demonstrated that tb1, which encodes a TCP transcription factor, is responsible for this transformation[18, 19]. Later studies showed that insertion of a Hopscotch transposon located ~60 kb upstream of tb1 enhances the expression of tb1 in maize, thereby repressing branch outgrowth[20, 21]. Through ChIP-seq and RNA-seq analyses, Dong et al.[22] demonstrated that tb1 acts to regulate multiple phytohormone signaling pathways (gibberellins, abscisic acid and jasmonic acid) and sugar sensing. Moreover, several other domestication loci, including teosinte glume architecture1 (tga1), prol1.1/grassy tillers1, were identified as its putative targets. Elucidating the precise regulatory mechanisms of these loci and signaling pathways will be an interesting and rewarding area of future research. Also worth noting, studies showed that tb1 and its homologous genes in Arabidopsis (Branched1 or BRC1) and rice (FINE CULM1 or FC1) play a conserved role in repressing the outgrowth of axillary branches in both dicotyledon and monocotyledon plants[23, 24].

    Teosinte ears possess two ranks of fruitcase-enclosed kernels, while maize produces hundreds of naked kernels on the ear[13]. tga1, which encodes a squamosa-promoter binding protein (SBP) transcription factor, underlies this transformation[25]. It has been shown that a de novo mutation occurred during maize domestication, causing a single amino acid substitution (Lys to Asn) in the TGA1 protein, altering its binding activity to its target genes, including a group of MADS-box genes that regulate glume identity[26].

    Prolificacy, the number of ears per plants, is also a domestication trait. It has been shown that grassy tillers 1 (gt1), which encodes an HD-ZIP I transcription factor, suppresses prolificacy by promoting lateral bud dormancy and suppressing elongation of the later ear branches[27]. The expression of gt1 is induced by shading and requires the activity of tb1, suggesting that gt1 acts downstream of tb1 to mediate the suppressed branching activity in response to shade. Later studies mapped a large effect QTL for prolificacy (prol1.1) to a 2.7 kb 'causative region' upstream of the gt1gene[28]. In addition, a recent study identified a new QTL, qEN7 (for ear number on chromosome 7). Zm00001d020683, which encodes a putative INDETERMINATE DOMAIN (IDD) transcription factor, was identified as the likely candidate gene based on its expression pattern and signature of selection during maize improvement[29]. However, its functionality and regulatory relationship with tb1 and gt1 remain to be elucidated.

    Smaller leaf angle and thus more compact plant architecture is a desired trait for modern maize varieties. Tian et al.[30] used a maize-teosinte BC2S3 population and cloned two QTLs (Upright Plant Architecture1 and 2 [UPA1 and UPA2]) that regulate leaf angle. Interestingly, the authors showed that the functional variant of UPA2 is a 2-bp InDel located 9.5 kb upstream of ZmRAVL1, which encodes a B3 domain transcription factor. The 2-bp Indel flanks the binding site of the transcription factor Drooping Leaf1 (DRL1)[31], which represses ZmRAVL1 expression through interacting with Liguleless1 (LG1), a SBP-box transcription factor essential for leaf ligule and auricle development[32]. UPA1 encodes brassinosteroid C-6 oxidase1 (brd1), a key enzyme for biosynthesis of active brassinolide (BR). The teosinte-derived allele of UPA2 binds DRL1 more strongly, leading to lower expression of ZmRAVL1 and thus, lower expression of brd1 and BR levels, and ultimately smaller leaf angle. Notably, the authors demonstrated that the teosinte-derived allele of UPA2 confers enhanced yields under high planting densities when introgressed into modern maize varieties[30, 33].

    Maize plants exhibit salient vegetative phase change, which marks the vegetative transition from the juvenile stage to the adult stage, characterized by several changes in maize leaves produced before and after the transition, such as production of leaf epicuticular wax and epidermal hairs. Previous studies reported that Glossy15 (Gl15), which encodes an AP2-like transcription factor, promotes juvenile leaf identity and suppressing adult leaf identity. Ectopic overexpression of Gl15 causes delayed vegetative phase change and flowering, while loss-of-function gl15 mutant displayed earlier vegetative phase change[34]. In another study, Gl15 was identified as a major QTL (qVT9-1) controlling the difference in the vegetative transition between maize and teosinte. Further, it was shown that a pre-existing low-frequency standing variation, SNP2154-G, was selected during domestication and likely represents the causal variation underlying differential expression of Gl15, and thus the difference in the vegetative transition between maize and teosinte[35].

    A number of studies documented evidence that tassels replace upper ears1 (tru1) is a key regulator of the conversion of the male terminal lateral inflorescence (tassel) in teosinte to a female terminal inflorescence (ear) in maize. tru1 encodes a BTB/POZ ankyrin repeat domain protein, and it is directly targeted by tb1, suggesting their close regulatory relationship[36]. In addition, a number of regulators of maize inflorescence morphology, were also shown as selective targets during maize domestication, including ramosa1 (ra1)[37, 38], which encodes a putative transcription factor repressing inflorescence (the ear and tassel) branching, Zea Agamous-like1 (zagl1)[39], which encodes a MADS-box transcription factor regulating flowering time and ear size, Zea floricaula leafy2 (zfl2, homologue of Arabidopsis Leafy)[40, 41], which likely regulates ear rank number, and barren inflorescence2 (bif2, ortholog of the Arabidopsis serine/threonine kinase PINOID)[42, 43], which regulates the formation of spikelet pair meristems and branch meristems on the tassel. The detailed regulatory networks of these key regulators of maize inflorescence still remain to be further elucidated.

    Kernel row number (KRN) and kernel weight are two important determinants of maize yield. A number of domestication genes modulating KRN and kernel weight have been identified and cloned, including KRN1, KRN2, KRN4 and qHKW1. KRN4 was mapped to a 3-kb regulatory region located ~60 kb downstream of Unbranched3 (UB3), which encodes a SBP transcription factor and negatively regulates KRN through imparting on multiple hormone signaling pathways (cytokinin, auxin and CLV-WUS)[44, 45]. Studies have also shown that a harbinger TE in the intergenic region and a SNP (S35) in the third exon of UB3 act in an additive fashion to regulate the expression level of UB3 and thus KRN[46].

    KRN1 encodes an AP2 transcription factor that pleiotropically affects plant height, spike density and grain size of maize[47], and is allelic to ids1/Ts6 (indeterminate spikelet 1/Tassel seed 6)[48]. Noteworthy, KRN1 is homologous to the wheat domestication gene Q, a major regulator of spike/spikelet morphology and grain threshability in wheat[49].

    KRN2 encodes a WD40 domain protein and it negatively regulates kernel row number[50]. Selection in a ~700-bp upstream region (containing the 5’UTR) of KRN2 during domestication resulted in reduced expression and thus increased kernel row number. Interestingly, its orthologous gene in rice, OsKRN2, was shown also a selected gene during rice domestication to negatively regulate secondary panicle branches and thus grain number. These observations suggest convergent selection of yield-related genes occurred during parallel domestication of cereal crops.

    qHKW1 is a major QTL for hundred-kernel weight (HKW)[51]. It encodes a CLAVATA1 (CLV1)/BARELY ANY MERISTEM (BAM)-related receptor kinase-like protein positively regulating HKW. A 8.9 Kb insertion in its promoter region was find to enhance its expression, leading to enhanced HKW[52]. In addition, Chen et al.[53] reported cloning of a major QTL for kernel morphology, qKM4.08, which encodes ZmVPS29, a retromer complex component. Sequencing and association analysis revealed that ZmVPS29 was a selective target during maize domestication. They authors also identified two significant polymorphic sites in its promoter region significantly associated with the kernel morphology. Moreover, a strong selective signature was detected in ZmSWEET4c during maize domestication. ZmSWEET4c encodes a hexose transporter protein functioning in sugar transport across the basal endosperm transfer cell layer (BETL) during seed filling[54]. The favorable alleles of these genes could serve as valuable targets for genetic improvement of maize yield.

    In a recent effort to more systematically analyze teosinte alleles that could contribute to yield potential of maize, Wang et al.[55] constructed four backcrossed maize-teosinte recombinant inbred line (RIL) populations and conducted detailed phenotyping of 26 agronomic traits under five environmental conditions. They identified 71 QTL associated with 24 plant architecture and yield related traits through inclusive composite interval mapping. Interestingly, they identified Zm00001eb352570 and Zm00001eb352580, both encode ethylene-responsive transcription factors, as two key candidate genes regulating ear height and the ratio of ear to plant height. Chen et al.[56] constructed a teosinte nested association mapping (TeoNAM) population, and performed joint-linkage mapping and GWAS analyses of 22 domestication and agronomic traits. They identified the maize homologue of PROSTRATE GROWTH1, a rice domestication gene controlling the switch from prostrate to erect growth, is also a QTL associated with tillering in teosinte and maize. Additionally, they also detected multiple QTL for days-to-anthesis (such as ZCN8 and ZmMADS69) and other traits (such as tassel branch number and tillering) that could be exploited for maize improvement. These lines of work highlight again the value of mining the vast amounts of superior alleles hidden in teosinte for future maize genetic improvement.

    Loss of seed shattering was also a key trait of maize domestication, like in other cereals. shattering1 (sh1), which encodes a zinc finger and YABBY domain protein regulating seed shattering. Interesting, sh1 was demonstrated to undergo parallel domestication in several cereals, including rice, maize, sorghum, and foxtail millet[57]. Later studies showed that the foxtail millet sh1 gene represses lignin biosynthesis in the abscission layer, and that an 855-bp Harbinger transposable element insertion in sh1 causes loss of seed shattering in foxtail millet[58].

    In addition to morphological traits, a number of physiological and nutritional related traits have also been selected during maize domestication. Based on survey of the nucleotide diversity, Whitt et al.[59] reported that six genes involved in starch metabolism (ae1, bt2, sh1, sh2, su1 and wx1) are selective targets during maize domestication. Palaisa et al.[60] reported selection of the Y1 gene (encoding a phytoene synthase) for increased nutritional value. Karn et al.[61] identified two, three, and six QTLs for starch, protein and oil respectively and showed that teosinte alleles can be exploited for the improvement of kernel composition traits in modern maize germplasm. Fan et at.[62] reported a strong selection imposed on waxy (wx) in the Chinese waxy maize population. Moreover, a recent exciting study reported the identification of a teosinte-derived allele of teosinte high protein 9 (Thp9) conferring increased protein level and nitrogen utilization efficiency (NUE). It was further shown that Thp9 encodes an asparagine synthetase 4 and that incorrect splicing of Thp9-B73 transcripts in temperate maize varieties is responsible for its diminished expression, and thus reduced NUE and protein content[63].

    Teosintes is known to confer superior disease resistance and adaptation to extreme environments (such as low phosphorus and high salinity). de Lange et al. and Lennon et al.[6466] reported the identification of teosinte-derived QTLs for resistance to gray leaf spot and southern leaf blight in maize. Mano & Omori reported that teosinte-derived QTLs could confer flooding tolerance[67]. Feng et al.[68] identified four teosinte-derived QTL that could improve resistance to Fusarium ear rot (FER) caused by Fusarium verticillioides. Recently, Wang et al.[69] reported a MYB transcription repressor of teosinte origin (ZmMM1) that confers resistance to northern leaf blight (NLB), southern corn rust (SCR) and gray leaf spot (GLS) in maize, while Zhang et al.[70] reported the identification of an elite allele of SNP947-G ZmHKT1 (encoding a sodium transporter) derived from teosinte can effectively improve salt tolerance via exporting Na+ from the above-ground plant parts. Gao et al.[71] reported that ZmSRO1d-R can regulate the balance between crop yield and drought resistance by increasing the guard cells' ROS level, and it underwent selection during maize domestication and breeding. These studies argue for the need of putting more efforts to tapping into the genetic resources hidden in the maize’s wild relatives. The so far cloned genes involved in maize domestication are summarized in Table 1. Notably, the enrichment of transcription factors in the cloned domestication genes highlights a crucial role of transcriptional re-wiring in maize domestication.

    Table 1.  Key domestication genes cloned in maize.
    GenePhenotypeFunctional annotationSelection typeCausative changeReferences
    tb1Plant architectureTCP transcription factorIncreased expression~60 kb upstream of tb1 enhancing expression[1822]
    tga1Hardened fruitcaseSBP-domain transcription factorProtein functionA SNP in exon (K-N)[25, 26]
    gt1Plant architectureHomeodomain leucine zipperIncreased expressionprol1.1 in 2.7 kb upstream of the promoter region increasing expression[27, 28]
    Zm00001d020683Plant architectureINDETERMINATE DOMAIN transcription factorProtein functionUnknown[29]
    UPA1Leaf angleBrassinosteroid C-6 oxidase1Protein functionUnknown[30]
    UPA2Leaf angleB3 domain transcription factorIncreased expressionA 2 bp indel in 9.5 kb upstream of ZmRALV1[30]
    Gl15Vegetative phase changeAP2-like transcription factorAltered expressionSNP2154: a stop codon (G-A)[34, 35]
    tru1Plant architectureBTB/POZ ankyrin repeat proteinIncreased expressionUnknown[36]
    ra1Inflorescence architectureTranscription factorAltered expressionUnknown[37, 38]
    zflPlant architectureTranscription factorAltered expressionUnknown[40, 41]
    UB3Kernel row numberSBP-box transcription factorAltered expressionA TE in the intergenic region;[4446]
    SNP (S35): third exon of UB3
    (A-G) increasing expression of UB3 and KRN
    KRN1/ids1/Ts6Kernel row numberAP2 Transcription factorIncreased expressionUnknown[47, 48]
    KRN2Kernel row numberWD40 domainDecreased expressionUnknown[50]
    qHKW1Kernel row weightCLV1/BAM-related receptor kinase-like proteinIncreased expression8.9 kb insertion upstream of HKW[51, 52]
    ZmVPS29Kernel morphologyA retromer complex componentProtein functionTwo SNPs (S-1830 and S-1558) in the promoter of ZmVPS29[53]
    ZmSWEET4cSeed fillingHexose transporterProtein functionUnknown[54]
    ZmSh1ShatteringA zinc finger and YABBY transcription factorProtein functionUnknown[57, 58]
    Thp9Nutrition qualityAsparagine synthetase 4 enzymeProtein functionA deletion in 10th intron of Thp9 reducing NUE and protein content[63]
    ZmMM1Biotic stressMYB Transcription repressorProtein functionUnknown[69]
    ZmHKT1Abiotic stressA sodium transporterProtein functionSNP947-G: a nonsynonymous variation increasing salt tolerance[70]
    ZmSRO1d-RDrought resistance and productionPolyADP-ribose polymerase and C-terminal RST domainProtein functionThree non-synonymous variants: SNP131 (A44G), SNP134 (V45A) and InDel433[71]
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    After its domestication from its wild progenitor teosinte in southwestern Mexico in the tropics, maize has now become the mostly cultivated crop worldwide owing to its extensive range expansion and adaptation to diverse environmental conditions (such as temperature and day length). A key prerequisite for the spread of maize from tropical to temperate regions is reduced photoperiod sensitivity[72]. It was recently shown that CENTRORADIALIS 8 (ZCN8), an Flowering Locus T (FT) homologue, underlies a major quantitative trait locus (qDTA8) for flowering time[73]. Interestingly, it has been shown that step-wise cis-regulatory changes occurred in ZCN8 during maize domestication and post-domestication expansion. SNP-1245 is a target of selection during early maize domestication for latitudinal adaptation, and after its fixation, selection of InDel-2339 (most likely introgressed from Zea mays ssp. Mexicana) likely contributed to the spread of maize from tropical to temperate regions[74].

    ZCN8 interacts with the basic leucine zipper transcription factor DLF1 (Delayed flowering 1) to form the florigen activation complex (FAC) in maize. Interestingly, DFL1 was found to underlie qLB7-1, a flowering time QTL identified in a BC2S3 population of maize-teosinte. Moreover, it was shown that DLF1 directly activates ZmMADS4 and ZmMADS67 in the shoot apex to promote floral transition[75]. In addition, ZmMADS69 underlies the flowering time QTL qDTA3-2 and encodes a MADS-box transcription factor. It acts to inhibit the expression of ZmRap2.7, thereby relieving its repression on ZCN8 expression and causing earlier flowering. Population genetic analyses showed that DLF1, ZmMADS67 and ZmMADS69 are all targets of artificial selection and likely contributed to the spread of maize from the tropics to temperate zones[75, 76].

    In addition, a few genes regulating the photoperiod pathway and contributing to the acclimation of maize to higher latitudes in North America have been cloned, including Vgt1, ZmCCT (also named ZmCCT10), ZmCCT9 and ZmELF3.1. Vgt1 was shown to act as a cis-regulatory element of ZmRap2.7, and a MITE TE located ~70 kb upstream of Vgt1 was found to be significantly associated with flowering time and was a major target for selection during the expansion of maize to the temperate and high-latitude regions[7779]. ZmCCT is another major flowering-time QTL and it encodes a CCT-domain protein homologous to rice Ghd7[80]. Its causal variation is a 5122-bp CACTA-like TE inserted ~2.5 kb upstream of ZmCCT10[72, 81]. ZmCCT9 was identified a QTL for days to anthesis (qDTA9). A Harbinger-like TE located ~57 kb upstream of ZmCCT9 showed the most significant association with DTA and thus believed to be the causal variation[82]. Notably, the CATCA-like TE of ZmCCT10 and the Harbinger-like TE of ZmCCT9 are not observed in surveyed teosinte accessions, hinting that they are de novo mutations occurred after the initial domestication of maize[72, 82]. ZmELF3.1 was shown to underlie the flowering time QTL qFT3_218. It was demonstrated that ZmELF3.1 and its homolog ZmELF3.2 can form the maize Evening Complex (EC) through physically interacting with ZmELF4.1/ZmELF4.2, and ZmLUX1/ZmLUX2. Knockout mutants of Zmelf3.1 and Zmelf3.1/3.2 double mutant presented delayed flowering under both long-day and short-day conditions. It was further shown that the maize EC promote flowering through repressing the expression of several known flowering suppressor genes (e.g., ZmCCT9, ZmCCT10, ZmCOL3, ZmPRR37a and ZmPRR73), and consequently alleviating their inhibition on several maize florigen genes (ZCN8, ZCN7 and ZCN12). Insertion of two closely linked retrotransposon elements upstream of the ZmELF3.1 coding region increases the expression of ZmELF3.1, thus promoting flowering[83]. The increase frequencies of the causal TEs in Vgt1, ZmCCT10, ZmCCT9 and ZmELF3.1 in temperate maize compared to tropical maize highlight a critical role of these genes during the spread and adaptation of maize to higher latitudinal temperate regions through promoting flowering under long-day conditions[72,8183].

    In addition, Barnes et al.[84] recently showed that the High Phosphatidyl Choline 1 (HPC1) gene, which encodes a phospholipase A1 enzyme, contributed to the spread of the initially domesticated maize from the warm Mexican southwest to the highlands of Mexico and South America by modulating phosphatidylcholine levels. The Mexicana-derived allele harbors a polymorphism and impaired protein function, leading to accelerated flowering and better fitness in highlands.

    Besides the above characterized QTLs and genes, additional genetic elements likely also contributed to the pre-Columbia spreading of maize. Hufford et al.[85] proposed that incorporation of mexicana alleles into maize may helped the expansion of maize to the highlands of central Mexico based on detection of bi-directional gene flow between maize and Mexicana. This proposal was supported by a recent study showing evidence of introgression for over 10% of the maize genome from the mexicana genome[86]. Consistently, Calfee et al.[87] found that sequences of mexicana ancestry increases in high-elevation maize populations, supporting the notion that introgression from mexicana facilitating adaptation of maize to the highland environment. Moreover, a recent study examined the genome-wide genetic diversity of the Zea genus and showed that dozens of flowering-related genes (such as GI, BAS1 and PRR7) are associated with high-latitude adaptation[88]. These studies together demonstrate unequivocally that introgression of genes from Mexicana and selection of genes in the photoperiod pathway contributed to the spread of maize to the temperate regions.

    The so far cloned genes involved in pre-Columbia spread of maize are summarized in Fig. 2 and Table 2.

    Figure 2.  Genes involved in Pre-Columbia spread of maize to higher latitudes and the temperate regions. The production of world maize in 2020 is presented by the green bar in the map from Ritchie et al. (2023). Ritchie H, Rosado P, and Roser M. 2023. "Agricultural Production". Published online at OurWorldInData.org. Retrieved from: 'https:ourowrldindata.org/agricultural-production' [online Resource].
    Table 2.  Flowering time related genes contributing to Pre-Columbia spread of maize.
    GeneFunctional annotationCausative changeReferences
    ZCN8Florigen proteinSNP-1245 and Indel-2339 in promoter[73, 74]
    DLF1Basic leucine zipper transcription factorUnknown[75]
    ZmMADS69MADS-box transcription factorUnknown[76]
    ZmRap2.7AP2-like transcription factorMITE TE inserted ~70 kb upstream[7779]
    ZmCCTCCT-domain protein5122-bp CACTA-like TE inserted ~2.5 kb upstream[72,81]
    ZmCCT9CCT transcription factorA harbinger-like element at 57 kb upstream[82]
    ZmELF3.1Unknownwo retrotransposons in the promote[84]
    HPC1Phospholipase A1 enzymUnknown[83]
    ZmPRR7UnknownUnknown[88]
    ZmCOL9CO-like-transcription factorUnknown[88]
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    Subsequent to domestication ~9,000 years ago, maize has been continuously subject to human selection during the post-domestication breeding process. Through re-sequencing analysis of 35 improved maize lines, 23 traditional landraces and 17 wild relatives, Hufford et al.[15] identified 484 and 695 selective sweeps during maize domestication and improvement, respectively. Moreover, they found that about a quarter (23%) of domestication sweeps (107) were also selected during improvement, indicating that a substantial portion of the domestication loci underwent continuous selection during post-domestication breeding.

    Genetic improvement of maize culminated in the development of high planting density tolerant hybrid maize to increase grain yield per unit land area[89, 90]. To investigate the key morphological traits that have been selected during modern maize breeding, we recently conducted sequencing and phenotypic analyses of 350 elite maize inbred lines widely used in the US and China over the past few decades. We identified four convergently improved morphological traits related to adapting to increased planting density, i.e., reduced leaf angle, reduced tassel branch number (TBN), reduced relative plant height (EH/PH) and accelerated flowering. Genome-wide Association Study (GWAS) identified a total of 166 loci associated with the four selected traits, and found evidence of convergent increases in allele frequency at putatively favorable alleles for the identified loci. Moreover, genome scan using the cross-population composite likelihood ratio approach (XP-CLR) identified a total of 1,888 selective sweeps during modern maize breeding in the US and China. Gene ontology analysis of the 5,356 genes encompassed in the selective sweeps revealed enrichment of genes related to biosynthesis or signaling processes of auxin and other phytohormones, and in responses to light, biotic and abiotic stresses. This study provides a valuable resource for mining genes regulating morphological and physiological traits underlying adaptation to high-density planting[91].

    In another study, Li et al.[92] identified ZmPGP1 (ABCB1 or Br2) as a selected target gene during maize domestication and genetic improvement. ZmPGP1 is involved in auxin polar transport, and has been shown to have a pleiotropic effect on plant height, stalk diameter, leaf length, leaf angle, root development and yield. Sequence and phenotypic analyses of ZmPGP1 identified SNP1473 as the most significant variant for kernel length and ear grain weight and that the SNP1473T allele is selected during both the domestication and improvement processes. Moreover, the authors identified a rare allele of ZmPGP1 carrying a 241-bp deletion in the last exon, which results in significantly reduced plant height and ear height and increased stalk diameter and erected leaves, yet no negative effect on yield[93], highlighting a potential utility in breeding high-density tolerant maize cultivars.

    Shade avoidance syndrome (SAS) is a set of adaptive responses triggered when plants sense a reduction in the red to far-red light (R:FR) ratio under high planting density conditions, commonly manifested by increased plant height (and thus more prone to lodging), suppressed branching, accelerated flowering and reduced resistance to pathogens and pests[94, 95]. High-density planting could also cause extended anthesis-silking interval (ASI), reduced tassel size and smaller ear, and even barrenness[96, 97]. Thus, breeding of maize cultivars of attenuated SAS is a priority for adaptation to increased planting density.

    Extensive studies have been performed in Arabidopsis to dissect the regulatory mechanism of SAS and this topic has been recently extensively reviewed[98]. We recently showed that a major signaling mechanism regulating SAS in Arabidopsis is the phytochrome-PIFs module regulates the miR156-SPL module-mediated aging pathway[99]. We proposed that in maize there might be a similar phytochrome-PIFs-miR156-SPL regulatory pathway regulating SAS and that the maize SPL genes could be exploited as valuable targets for genetic improvement of plant architecture tailored for high-density planting[100].

    In support of this, it has been shown that the ZmphyBs (ZmphyB1 and ZmphyB2), ZmphyCs (ZmphyC1 and ZmphyC2) and ZmPIFs are involved in regulating SAS in maize[101103]. In addition, earlier studies have shown that as direct targets of miR156s, three homologous SPL transcription factors, UB2, UB3 and TSH4, regulate multiple agronomic traits including vegetative tillering, plant height, tassel branch number and kernel row number[44, 104]. Moreover, it has been shown that ZmphyBs[101, 105] and ZmPIF3.1[91], ZmPIF4.1[102] and TSH4[91] are selective targets during modern maize breeding (Table 3).

    Table 3.  Selective genes underpinning genetic improvement during modern maize breeding.
    GenePhenotypeFunctional annotationSelection typeCausative changeReferences
    ZmPIF3.1Plant heightBasic helix-loop-helix transcription factorIncreased expressionUnknown[91]
    TSH4Tassel branch numberTranscription factorAltered expressionUnknown[91]
    ZmPGP1Plant architectureATP binding cassette transporterAltered expressionA 241 bp deletion in the last exon of ZmPGP1[92, 93]
    PhyB2Light signalPhytochrome BAltered expressionA 10 bp deletion in the translation start site[101]
    ZmPIF4.1Light signalBasic helix-loop-helix transcription factorAltered expressionUnknown[102]
    ZmKOB1Grain yieldGlycotransferase-like proteinProtein functionUnknown[121]
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    In a recent study to dissect the signaling process regulating inflorescence development in response to the shade signal, Kong et al.[106] compared the gene expression changes along the male and female inflorescence development under simulated shade treatments and normal light conditions, and identified a large set of genes that are co-regulated by developmental progression and simulated shade treatments. They found that these co-regulated genes are enriched in plant hormone signaling pathways and transcription factors. By network analyses, they found that UB2, UB3 and TSH4 act as a central regulatory node controlling maize inflorescence development in response to shade signal, and their loss-of-function mutants exhibit reduced sensitivity to simulated shade treatments. This study provides a valuable genetic source for mining and manipulating key shading-responsive genes for improved tassel and ear traits under high density planting conditions.

    Nowadays, global maize production is mostly provided by hybrid maize, which exhibits heterosis (or hybrid vigor) in yields and stress tolerance over open-pollinated varieties[3]. Hybrid maize breeding has gone through several stages, from the 'inbred-hybrid method' stage by Shull[107] and East[108] in the early twentieth century, to the 'double-cross hybrids' stage (1930s−1950s) by Jones[109], and then the 'single-cross hybrids' stage since the 1960s. Since its development, single-cross hybrid was quickly adopted globally due to its superior heterosis and easiness of production[3].

    Single-cross maize hybrids are produced from crossing two unrelated parental inbred lines (female × male) belonging to genetically distinct pools of germplasm, called heterotic groups. Heterotic groups allow better exploitation of heterosis, since inter-group hybrids display a higher level of heterosis than intra-group hybrids. A specific pair of female and male heterotic groups expressing pronounced heterosis is termed as a heterotic pattern[110, 111]. Initially, the parental lines were derived from a limited number of key founder inbred lines and empirically classified into different heterotic groups (such as SSS and NSS)[112]. Over time, they have expanded dramatically, accompanied by formation of new 'heterotic groups' (such as Iodent, PA and PB). Nowadays, Stiff Stalk Synthetics (SSS) and PA are generally used as FHGs (female heterotic groups), while Non Stiff Stalk (NSS), PB and Sipingtou (SPT) are generally used as the MHGs (male heterotic groups) in temperate hybrid maize breeding[113].

    With the development of molecular biology, various molecular markers, ranging from RFLPs, SSRs, and more recently high-density genome-wide SNP data have been utilized to assign newly developed inbred lines into various heterotic groups, and to guide crosses between heterotic pools to produce the most productive hybrids[114116]. Multiple studies with molecular markers have suggested that heterotic groups have diverged genetically over time for better heterosis[117120]. However, there has been a lack of a systematic assessment of the effect and contribution of breeding selection on phenotypic improvement and the underlying genomic changes of FHGs and MHGs for different heterotic patterns on a population scale during modern hybrid maize breeding.

    To systematically assess the phenotypic improvement and the underlying genomic changes of FHGs and MHGs during modern hybrid maize breeding, we recently conducted re-sequencing and phenotypic analyses of 21 agronomic traits for a panel of 1,604 modern elite maize lines[121]. Several interesting observations were made: (1) The MHGs experienced more intensive selection than the FMGs during the progression from era I (before the year 2000) to era II (after the year 2000). Significant changes were observed for 18 out of 21 traits in the MHGs, but only 10 of the 21 traits showed significant changes in the FHGs; (2) The MHGs and FHGs experienced both convergent and divergent selection towards different sets of agronomic traits. Both the MHGs and FHGs experienced a decrease in flowering time and an increase in yield and plant architecture related traits, but three traits potentially related to seed dehydration rate were selected in opposite direction in the MHGs and FHGs. GWAS analysis identified 4,329 genes associated with the 21 traits. Consistent with the observed convergent and divergent changes of different traits, we observed convergent increase for the frequencies of favorable alleles for the convergently selected traits in both the MHGs and FHGs, and anti-directional changes for the frequencies of favorable alleles for the oppositely selected traits. These observations highlight a critical contribution of accumulation of favorable alleles to agronomic trait improvement of the parental lines of both FHGs and MHGs during modern maize breeding.

    Moreover, FST statistics showed increased genetic differentiation between the respective MHGs and FHGs of the US_SS × US_NSS and PA × SPT heterotic patterns from era I to era II. Further, we detected significant positive correlations between the number of accumulated heterozygous superior alleles of the differentiated genes with increased grain yield per plant and better parent heterosis, supporting a role of the differentiated genes in promoting maize heterosis. Further, mutational and overexpressional studies demonstrated a role of ZmKOB1, which encodes a putative glycotransferase, in promoting grain yield[121]. While this study complemented earlier studies on maize domestication and variation maps in maize, a pitfall of this study is that variation is limited to SNP polymorphisms. Further exploitation of more variants (Indels, PAVs, CNVs etc.) in the historical maize panel will greatly deepen our understanding of the impact of artificial selection on the maize genome, and identify valuable new targets for genetic improvement of maize.

    The ever-increasing worldwide population and anticipated climate deterioration pose a great challenge to global food security and call for more effective and precise breeding methods for crops. To accommodate the projected population increase in the next 30 years, it is estimated that cereal production needs to increase at least 70% by 2050 (FAO). As a staple cereal crop, breeding of maize cultivars that are not only high-yielding and with superior quality, but also resilient to environmental stresses, is essential to meet this demand. The recent advances in genome sequencing, genotyping and phenotyping technologies, generation of multi-omics data (including genomic, phenomic, epigenomic, transcriptomic, proteomic, and metabolomic data), creation of novel superior alleles by genome editing, development of more efficient double haploid technologies, integrating with machine learning and artificial intelligence are ushering the transition of maize breeding from the Breeding 3.0 stage (biological breeding) into the Breeding 4.0 stage (intelligent breeding)[122, 123]. However, several major challenges remain to be effectively tackled before such a transition could be implemented. First, most agronomic traits of maize are controlled by numerous small-effect QTL and complex genotype-environment interactions (G × E). Thus, elucidating the contribution of the abundant genetic variation in the maize population to phenotypic plasticity remains a major challenge in the post-genomic era of maize genetics and breeding. Secondly, most maize cultivars cultivated nowadays are hybrids that exhibit superior heterosis than their parental lines. Hybrid maize breeding involves the development of elite inbred lines with high general combining ability (GCA) and specific combining ability (SCA) that allows maximal exploitation of heterosis. Despite much effort to dissect the mechanisms of maize heterosis, the molecular basis of maize heterosis is still a debated topic[124126]. Thirdly, only limited maize germplasm is amenable to genetic manipulation (genetic transformation, genome editing etc.), which significantly hinders the efficiency of genetic improvement. Development of efficient genotype-independent transformation procedure will greatly boost maize functional genomic research and breeding. Noteworthy, the Smart Corn System recently launched by Bayer is promised to revolutionize global corn production in the coming years. At the heart of the new system is short stature hybrid corn (~30%−40% shorter than traditional hybrids), which offers several advantages: sturdier stems and exceptional lodging resistance under higher planting densities (grow 20%−30% more plants per hectare), higher and more stable yield production per unit land area, easier management and application of plant protection products, better use of solar energy, water and other natural resources, and improved greenhouse gas footprint[127]. Indeed, a new age of maize green revolution is yet to come!

    This work was supported by grants from the Key Research and Development Program of Guangdong Province (2022B0202060005), National Natural Science Foundation of China (32130077) and Hainan Yazhou Bay Seed Lab (B21HJ8101). We thank Professors Hai Wang (China Agricultural University) and Jinshun Zhong (South China Agricultural University) for valuable comments and helpful discussion on the manuscript. We apologize to authors whose excellent work could not be cited due to space limitations.

  • The authors declare that they have no conflict of interest. Haiyang Wang is an Editorial Board member of Seed Biology who was blinded from reviewing or making decisions on the manuscript. The article was subject to the journal's standard procedures, with peer-review handled independently of this Editorial Board member and his research groups.

  • Supplemental Table S1 Standard calibration curve equation and R2 (coefficient of determination) values used for analysis of biochemical parameters.
    Supplemental Fig. S1 Graphical abstract.
    Supplemental Fig. S2 HPLC chromatograms of mixed standard solution and green tea extracts processed by different methods.
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  • Cite this article

    Adhikary B, Kashyap B, Kanrar B, Gogoi RC, Varghese S, et al. 2024. Comparative evaluation of the impact of processing methods in determining the levels of health promoting chemical constituents and quality of green tea. Beverage Plant Research 4: e027 doi: 10.48130/bpr-0024-0016
    Adhikary B, Kashyap B, Kanrar B, Gogoi RC, Varghese S, et al. 2024. Comparative evaluation of the impact of processing methods in determining the levels of health promoting chemical constituents and quality of green tea. Beverage Plant Research 4: e027 doi: 10.48130/bpr-0024-0016

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Comparative evaluation of the impact of processing methods in determining the levels of health promoting chemical constituents and quality of green tea

Beverage Plant Research  4 Article number: e027  (2024)  |  Cite this article

Abstract: The first step of green tea manufacture involves enzyme deactivation by heat application. The present study investigated the effects of various fixing and processing methods viz. steam-roasting (S-6), pan-firing (P-8), blanching (B-2), and CTC cuts after steam-roasting (S-CTC), on the bio-chemical profiles and organoleptic quality of green teas processed differently into orthodox and CTC types, from region-specific tea cultivars, suitable for green tea production under agroclimatic condition of Dooars, West Bengal, India. Differences in fixing method and processing style showed notable variation (p ≤ 0.05) in the chemical quality indicators of green tea viz. Total catechin, polyphenol, flavonoid, and water extract content among the differently processed green teas. The most significant finding of the study revealed that when B-2 is employed for deactivation, it resulted in a substantial reduction (47%−52%) of caffeine levels without affecting the catechins content and antioxidant potential of green tea samples when compared to S-6 and P-8 methods. Interestingly, our results demonstrated significantly higher water extract values (42.19% dry weight) in green CTC teas and lower values in B-2 green tea samples (33.67%), as compared to S-8 and P-8 green teas, which received better taster ratings (≥ 7). These findings have highlighted the role of processing method and the impact of fixing technique in determining the contents of health-promoting attributes and taste quality of green teas, thus providing diverse choices to tea producers and consumers to opt for specific green tea products and expediting the need to further explore its commercial application in the nutraceutical and pharmaceutical industry (Supplemental Fig. S1).

    • Green tea is an un-aerated product made from the tender shoots of the tea plant (Camellia sinensis L.). Unlike black tea, the processing technique employed for green tea production omits the oxidation stage by fixing enzymes, allowing the tea to remain green in color which leads to an assortment of external and inner qualities[1]. Green tea production employs both Chinese and Japanese-style processing methods. Steaming is preferred in Japan and India, whereas the pan-firing method is popular in China and Korea. It has been previously reported that differences in processing methods impart distinguishable changes in the biochemical profile and taste quality of green teas[2]. Green tea processed in orthodox forms requires hand or machine-assisted rolling of deactivated tea leaves to obtain relatively bigger-sized tea particles, but in the CTC method, the fixing step is followed by complete maceration of the tea leaves to produce smaller-sized granular particles. Green tea fixing methods like steaming, pan-firing, and blanching have developed over the years depending on cultural variability, market acceptability, and end-user preference[3]. The fixing stage of enzyme deactivation along with the rolling step, in which leaves are curled and twisted, are considered important technical parameters to attain desirable quality in green tea. Monitoring the initial fixing step at elevated temperatures during green tea production, is crucial to avoid catechin oxidation that is responsible for the astringency and bitterness of green teas, during storage[4]. It has been reported that over-fixing increases the amino acid content due to rapid protein hydrolysis, scorches the leaf and results in a smoky taste and a higher ratio of broken leaf whereas under-fixing results in the browning of green teas upon storage due to residual enzyme activities[2]. Research studies suggest that bigger-sized orthodox green teas retain more moisture and are more likely to be oxidized, reducing their storage life and extraction efficiency, whereas, in contrast, the CTC teas' increased surface area causes smaller particles to interact with water more during brewing, which increases the extraction efficiency of the final brew and therefore has been found to be suitable for ready-to-drink dip tea sachets[5]. Production of green CTC tea has been shown to be a simple, better recovery and less time-consuming method[6], wherein, the teas exhibited bright green colour and more cuppage. The blending and mixing of herbs for desirable flavors become easier with the smaller-sized CTC tea granules. Ready-to-drink flavoured CTC green tea variants are becoming popular nowadays and present competitive and customer-appealing products in the market. Few researchers have reported that the type and quality of the green tea reflected by its chemical composition and the soluble solids extracted during infusion not only depend upon genetic character and temperature of infusion but are also affected by multifarious biochemical changes within the tea leaves during fixing as well as harvesting and subsequent processing conditions[3,7]. Primary leaf biochemicals imparting the taste characteristics and health-attributes of green tea include catechin polyphenols, caffeine, free amino acids, chlorophyll and other compounds jointly or separately[8]. The water-soluble extracts of green tea are the main compounds responsible for bioactivity and the associated medicinal benefits[9].

      Scientific investigations on tea biochemicals in recent years have justified the ancient belief of health promoting benefits of green tea consumption[10], which is gaining popularity among the wider community. Increased mass media propaganda on the medicinal health-promoting effects linked with green tea consumption has created a lucrative market potential. As a popular non-alcoholic beverage, green tea products with diverse physical and chemical quality parameters would be equally beneficial to tea manufacturers and consumers.

      Ensuing the futuristic trend of the Indian tea industry, there is a scope for Dooars tea estates to divert attention to these alternative ways of green tea processing as well as its promotion to capture the domestic market domain. Recent findings have generated information on region-specific green tea suitable cultivars[11], however, a detailed scientific study in terms of biochemical constituents and organoleptic taste profiles of differentially fixed and processed orthodox and CTC green teas has not been addressed under Dooars agroclimatic conditions. Therefore, the present study was conducted to investigate the impact of various fixing methods viz. steaming, pan-firing, and blanching for orthodox and CTC green teas, in determining the anti-oxidative and health-promoting biochemical profiles, by keeping minimal variations in cultivars, plucking, and other technical aspects of process-parameters.

    • All the chemicals used for this study were of analytical grade. Miniature manufacturing was carried out using a mini-CTC machine (Mesco Equipment) with a 10 tpi (tooth-per-inch) roller. UV-VIS spectrophotometer (Cary Bio 50) was used for biochemical analysis. HPLC analyses (Agilent 1260 infinity UPLC) for the estimation of catechin fractions and caffeine were carried out.

    • The Dooars region is situated in the Himalayan foothills and has loamy to sandy loam type and silt clay type of soil. Tea cultivars used in the study were grown in the trial plot of our center, situated at 26°54' North Latitude and 88°54′ East Longitude with an elevation of 226.60 m. Long-term weather data showed a daily temperature range of 18.7 to 28.8 °C, humidity levels of 91.5% (morning) and 64.2% (evening), 5.72 h average sunshine, and approximately 3,800 mm of annual rainfall. Monsoon commences from May-June and lasts until September, followed by cold winters. During the period of our study from July to September, the maximum and minimum temperatures were 31.3 to 32.3 °C and 20.5 to 21.8 °C respectively with corresponding precipitation recorded between 867.7 to 1,058.2 mm. The experimental plot received the balanced fertilizers of nitrogen, phosphorus, and potassium in two splits at a ratio of 110:25:110, as recommended for tea cultivation in this region[12].

    • Locally grown tea cultivars viz. Tocklai Vegetative (TV)-9, TV-20, Teenali (TA)-17/1/54, and Tocklai Stock (TS)-462 of similar age from our experimental plots were used for green tea processing. These cultivars were selected based on previous studies on the suitability of these cultivars for green tea production[11,13]. Leaf quality of 50%−60% fineness, was maintained. Three sets of green tea samples were processed by different methods, on three separate occasions, during July, August, and September respectively, coinciding with monsoon flush, and subsequently analyzed for chemical and sensory parameters.

    • The leaf samples in equal proportions from each cultivar were mixed and then divided into four parts of 0.5 kg each. Green tea processing of the orthodox and CTC-type was done in a miniature factory set-up by various methods, which included conventional steam-roasting, pan-firing, blanching, and steam-roasting followed by 2 cut CTC, with minor simplified modifications as follows.

    • Green tea was processed by steaming in a perforated chamber at 105 ± 5 °C for 6−8 min, depending on leaf standard. The steamed leaves were surface dried and cooled by blowing air for 15 min, rolled in a peizzy roller for 30 min and finally dried in a cabinet drier at 110 °C for 40 min[13].

    • Fresh leaves were deactivated by pan-firing in an electric panner at 250 ± 10 °C for 8−10 min, depending on leaf standard, cooled by blowing air for 15 min, rolled in a peizzy roller for 30 min and finally dried in a cabinet drier at 110 °C for 40 min[11].

    • Fresh leaves were fixed by dipping in boiling distilled water for 1−2 min depending on leaf standard. The subsequent procedure was similar to the conventional steam-roasting method.

    • Fresh leaves were deactivated by steaming in a perforated chamber at 105 ± 5 °C for 6−8 min, depending on leaf standard. The steamed leaves were surface dried and cooled by blowing air for 15 min, rolled in a peizzy roller for 30 min prior to cutting in a mini-CTC machine for twice (2-cut). Final drying was carried out in a cabinet drier at 110 °C for 40 min.

    • Extraction of green tea catechins was carried out following the ISO method[14]. Samples were finely grounded in a mortar-pestle, and 0.2 g samples were taken in graded tubes. To the sample, 5 mL of 70% (v/v) pre-heated (70 °C) methanol/water extraction mixture was added and mixed thoroughly on a vortex mixer (Remi). The tubes were put in a water bath at 70 °C (10 min), followed by mixing in a vortex mixer after 5 and 10 min, respectively, and then cooled to room temperature, before centrifugation (3,500 rpm, 10 min) (Remi). After decanting the supernatant in a graduated tube, the residue was extracted a second time with 5 mL of extraction mixture. The extracts were then mixed and concentrated to a volume of 10 mL using the methanol/water extraction mixture. For catechin analysis by HPLC, 1 mL of sample extract was mixed with 4 mL of stabilizing solution (10% v/v acetonitrile with 500 μg/mL EDTA and ascorbic acid), and filtered through a 0.45 μm filter and injected.

      Individual catechins, gallic acid and caffeine was analyzed using Agilent 1260 infinity series HPLC equipped with Zorbax Eclipsed plus Phenyl-Hexyl column (4.6 mm × 250 mm, 5 μm) and Agilent Zorbax Eclipsed Plus Phenyl-Hexyl guard column (4.6 × 12.5 mm, 5 μm), in accordance with the ISO method[14]. Different ratios of water, acetonitrile, and acetic acid solvents were employed for mobile phase A (89:9:2) and mobile phase B (18:2:80). Both the mobile phases received an addition of EDTA (20 μg/mL). The injection volume was 20 μl. Flow rate, column temperature and detection wavelength were set to 1 mL/min, 35 ± 0.5 °C, and 278 nm respectively. A binary gradient condition was initiated with 100% mobile phase A for 10 min, followed by a linear gradient over a period of 15 min to 68% mobile phase A and 32% mobile phase B, which was run and maintained for 10 min. The system was then reset to 100% mobile phase A and given 10 min to equilibrate before the next injection. Catechin and caffeine peaks were identified by comparing retention times from sample chromatograms with those obtained from the mixed standard solutions under the same chromatographic conditions.

      Quantification of individual catechins, gallic acid and caffeine was done by using the Relative Response Factors (RRFs) values for catechins and gallic acid with respect to caffeine and comparing the peak area of individual components to the caffeine calibration graph (Supplemental Table S1) as described[14].

    • Folin-Ciocalteau reagent was used to estimate the total polyphenol content by the ISO method[15]. Approximately, 0.2 g of well-ground green tea powder was extracted using a methanol-water (70−30) mixture, and the extract was then diluted to 100 times with water. To 1 mL of the diluted extract, 5 mL (10 % v/v) Folin-Ciocalteau reagent was added, followed by 4 mL of Sodium Carbonate solution (7.5% w/v), which was thoroughly mixed. The mixture was left to stand at room temperature for 1 h. The result of the absorbance measurement at 760 nm was reported as a weight percentage by the gallic acid standard calibration curve values (Supplemental Table S1).

    • TFC was estimated following the method described by Akbay et al.[16]. Powdered green tea sample (0.2 g) was extracted with methanol-water (70−30) mixture. One mL of this extract was diluted with 3 mL of methanol. To this diluted solution 0.2 ml of Aluminium Chloride (AlCl3, 1 M), 0.2 mL potassium acetate solution (10% w/v) and 5.6 mL distilled water were added and mixed well. Similarly, a sample blank was prepared by replacing AlCl3 with water. The absorbance reading was taken at 415 nm and the result was obtained by quercetin standard calibration curve values (Supplemental Table S1).

    • The water extract content in green tea samples was determined using the ISO method[17], with minor modifications, to evaluate the effect of process type in determining the water-soluble extract content. Briefly, the non-grounded orthodox and CTC green tea samples (2.0 g) were put in a 250 mL flask, and 200 mL hot distilled water was added and refluxed over low heat for 1 h, rotating the flask occasionally. The flask was repeatedly washed out with hot distilled water transferring all the insoluble residue into a pre-weighed crucible. Finally, the residue was washed with 200 mL of hot water. The residue was dried by suction. The crucible and its contents were heated in an oven at 103 ± 2 °C, for 16 h. The dessicator-cooled crucible with its content was weighed. The result was expressed as a weight% on a dry mass basis, as mentioned in ISO 9768:1994[17].

    • ISO 3103:2109[18] was followed in the preparation process of tea infusion and liquor. This method entails extracting soluble substances from 2.8 ± 0.2 g of dried tea leaves contained in a porcelain cup using 150 ml of freshly heated water, that is covered with a lid for 4−5 min for brewing. The liquor is then poured into the bowl through the serration in the lid cover to keep the infused leaf in the pot. The lid was removed and then inverted and the infused leaf was placed on it. The tea taster used a randomized method for the tasting, concealing the sample details in accordance with ISO 3163[19] and examined the infused leaf and liquor organoleptic qualities. Once the tea is cool enough, a tea taster uses a large spoon to noisily slurp the liquor into the lips, which guarantees a consistent taste profile by allowing adequate oxygen and tea to travel through the tongue's taste receptors[20]. The liquid was spit subsequently in a spittoon, before the next sample. The parameters of tea quality (color, strength, briskness, and brightness), manufacturing defect parameters, and field-related agro-practices have been described by FAO[21]. After taking these findings into account, the taster evaluated the tea's organoleptic quality in Hedonic scale ratings ranging from 0 to 10[11,22].

    • The DPPH antioxidant activity assay was carried out following a previously reported method[23], with slight modifications. Briefly, the powdered tea sample (0.2 g) was extracted with methanol-water (70−30) mixture. DPPH solution (0.1 mM in methanol, 4 mL) was added to 2 mL each of the different concentration of the extract (2.5, 5, 7.5, 10, 12.5, 15, and 20 μg/mL). The reaction mixture was incubated at room temperature for 30 min and absorbance readings were taken at 517 nm, with ascorbic acid (100 μg/mL) as positive control and methanol as blank. The inhibition ratio (i.e., the concentration of the tea extract required to reduce the absorbance of DPPH by 50%) of the sample was obtained using the following equation:

      Inhibition ratio (%) = {(Ac – As)/Ac} × 100; where, Ac = Absorbance of the control and As = Absorbance of the sample

      A plot of inhibition ratio against concentration gives a straight line from which IC50 was calculated.

    • The FRAP assay was performed following a previously reported method[24], with some modifications. Preparation of FRAP reagent was carried out by mixing 10 mM 2,4,6-Tripyridyl-S-triazine (TPTZ) in 40 mM HCl with 20 mM Ferric Chloride (FeCl3) in 300 mM acetate buffer. For the assay, 200 μL of tea extract, 1.8 mL of water and 4 mL FRAP reagent was mixed and the solution was incubated in the dark for 30 min. Then, the absorbance was taken at 593 nm using water as blank. The result was obtained by comparison with the Ferrous Sulphate (FeSO4) standard graph.

    • The data of each experimental analysis that was performed in triplicate was analyzed by one-way analysis of Variance (ANOVA). Mean values of the biochemical parameters were separated using Duncan's multiple test range (p ≤ 0.05). All values are represented as mean ± standard error (SE). Statistical analysis and correlations among the biochemical quality parameters were calculated by Pearson's correlation coefficient test using SPSS software (version 16.0., SPSS < Chicago, IL, USA).

    • The content of individual catechin fractions and total catechins, caffeine, gallic acid in green tea samples processed differently are presented in Table 1 and Fig. 1 respectively.

      Table 1.  Content (% dry weight) of non-gallated catechins viz. catechin +(C), epicatechin (EC) and epigallocatechin (EGC), gallated catechins viz. epicatechin gallate (ECG) and epigallocatechin gallate (EGCG), in green tea samples processed by different methods.

      Process type Catechin fractions Total catechins (TC)
      C EC EGC EGCG ECG
      S-6 0.99 ± 0.07 1.30 ± 0.06 3.87 ± 0.33 10.49 ± 0.57 2.84 ± 0.25 19.48 ± 0.44ab
      P-8 0.93 ± 0.03 1.46 ± 0.08 4.35 ± 0.31 10.84 ± 0.50 2.70 ± 0.14 20.26 ± 0.47b
      B-2 0.95 ± 0.05 1.39 ± 0.07 4.47 ± 0.40 10.79 ± 0.34 2.74 ± 0.25 20.33 ± 0.27b
      S-CTC 0.94 ± 0.05 1.43 ± 0.07 3.91 ± 0.21 9.84 ± 0.53 2.58 ± 0.21 18.69 ± 0.42a
      All values are represented as mean ± SE. Values within a column with different letters are significantly different by ANOVA with Duncan multiple test range at p < 0.05. C, (+)-catechin; EC, (−)-epicatechin; EGC, (−)-epigallocatechin; EGCG, (−)-epigallocatechin gallate; ECG, (−)-epicatechin gallate; TC, total catechins. S-6, steam-roasting for 6 min; P-8, panning for 8 min; B-2, blanching for 2 min; S-CTC, steam-roasting for 2 min followed by two CTC cuts.

      Figure 1. 

      Content (% dry weight) of gallic acid and caffeine of green tea samples processed by different methods. Values are represented as mean ± SE. Different lowercase letters on top of the bars indicate significant difference by ANOVA with Duncan multiple test range at p < 0.05; S-6, steam-roasting for 6 min; P-8, pan-firing for 8 min; B-2, blanching for 2 min; S-CTC, steam-roasting for 2 min followed by two CTC cuts.

      The data indicates that the processing method exhibits a significant impact on the chemical composition of green tea samples, especially caffeine. The content of epigallocatechin was found to be marginally higher in pan-fired and blanched-green teas than in steamed orthodox and CTC-mode processing. Although insignificant, the amounts of epigallocatechin gallate and epicatechin gallate were found to be notably higher in S-6, P-8, and B-2 as compared to S-CTC samples. However, significant differences were observed between the total catechin contents of S-CTC type green tea as compared to other process-type green teas, which may be attributed to the loss of gallated catechin fractions viz. epigallocatechin gallate and epicatechin gallate due to frictional heat generation at the crushing-tearing and curling step, that is congruent with a previous report that the level of green tea catechins is reduced due to epimerization and degradation during processing[25], and storage conditions such as temperature and relative humidity[2]. Contrary to our findings, higher total catechin content for CTC green tea than orthodox type has been detailed[26,27], the difference can be attributed to the diversity in tea cultivars, agroclimatic variation in the study and smaller size of CTC granules enhancing the extraction efficiency. It was noted that deactivation by blanching (B-2) reduced the caffeine content by 40%−50% as compared to other green tea processing types viz. S-6, P-8 and S-CTC respectively (Supplemental Fig. S2). Representative HPLC chromatographs of the mixed standards and green tea samples processed by different methods is mentioned in Supplemental Fig. S2.

      Our finding of significantly lower caffeine content of B-2 orthodox green tea (1.94%) as compared to other green tea types, is consistent with a previous report[27], where it was conferred that blanching tea leaves for 3 min eliminated 83% of the caffeine while retaining 95% of the catechins. It has been reported that the solubility of caffeine is very low in water at room temperature (2.2% w/w), however, in boiling water, the solubility of caffeine increases greatly (66.7% w/w). Specific removal of a significant amount of caffeine as compared to catechins, from fresh tea leaves during blanching, may be attributed to the higher solubility of caffeine in hot water and its lower molecular weight (21.7 g·L−1, 194.2 kDa) than the catechins (~ 5 g·L−1, 290−458 kDa), that allows caffeine molecules to diffuse through the cell membrane and hence, during the blanching step, a large amount of caffeine goes out of the leaf resulting in lower caffeine content in the green tea[28]. The results also indicated significant variation (p ≤ 0.05) in the gallic acid content of S-6 and P-8 orthodox green teas that could have occurred due to wet and dry mode of heat application and resulted in greater loss of gallic acid in steaming by wet-heat as compared to pan-firing.

      The combination of catechins with caffeine and gallic acid is often associated with green tea taste. Although caffeine intake has some proven health benefits, higher intake of caffeine can have a negative impact on the human central nervous system and is therefore contraindicated for children and pregnant women[29,30]. Moreover, studies have linked consumption of caffeine containing beverages with irritation of the gastrointestinal tract and sleeplessness[31]. There is persistent market demand for decaffeinated versions of tea and coffee beverages, therefore, caffeine reduction in the green tea manufacturing process is often desirable. Based on these findings, it can be suggested that fixation by blanching is one of the simple, non-toxic, and low-cost processes of decaffeinating green tea without removal of the catechin antioxidants.

    • The TPC and TFC in green teas processed by different methods is presented in Fig. 2. Significant variation in polyphenol content was observed for green tea samples processed by different fixing-methods and types.

      Figure 2. 

      Content (% dry weight) of total polyphenol, total flavonoid and water extract of green tea samples processed by different methods. Values are represented as mean ± SE. Different lowercase letters on top of the bars indicate significant difference by ANOVA with Duncan multiple test range at p < 0.05; TPC, Total Polyphenol Content; TFC, Total Flavonoid Content; WE, Water Extract; S-6, steam-roasting for 6 min; P-8, pan-firing for 8 min; B-2, blanching for 2 min; S-CTC, steam-roasting for 2 min followed by two CTC cuts.

      The conventional steam-roasting process (S-6) of orthodox green tea production retained the maximum polyphenols. Green teas (S-6, P-8, and S-CTC) exhibited higher polyphenol content (23.65%, 22.97%, and 22.50%) as compared to B-2 (21.90%). Similar data was obtained for TFC, wherein significant differences (p ≤ 0.05) were obtained for S-CTC and B-2 type green tea. The extraction rate of green tea polyphenols is influenced by the shape, size of tea leaves, and degree of destruction during the fixing of leaves and, usually the longer time of fixation during the steaming and panning method causes more destruction of leaves yielding more small particles compared to the shorter duration blanching process. The bi-directional rolling after fixation step aids the juices to spread out in steam-roasted green teas as compared to other methods. The CTC step after steaming leads to the loss of polyphenolic compounds because of prolonged processing[1]. Our results on differences of TPC and TFC content due to process-variation are in congruence with a previous finding[32], where the researchers inferred that thermal treatment by blanching resulted in transformation, as well as, loss of phenolic and flavonoid compounds due to leaching in water and therefore reduction in the phenolic and flavonoid content. Likewise, variation in polyphenol levels in the water infused extracts of green tea due to processing has also been described[33].

      Green tea polyphenols and flavonoids are key compounds conferring the antioxidative and therapeutic properties of tea consumption and also impart astringency and bitter taste to green tea infusion. The water-soluble polyphenols and flavonoids have the potential used singly or in combination with other active principles in the food, pharmaceutical, and cosmetic industries[10]. The health value of green tea beverages is determined, among others, by the content of polyphenolic substances, therefore, in summary, the conventional methods of steam-roasting and pan-firing are best suited to conserve polyphenols and flavonoids in green tea products.

    • Water extract content is a quality indicator that constitutes the phenolics, alkaloids, amino acids, and many minor water-soluble substances extracted from the tea samples which determines the quality and cuppage of the tea, and is employed in the tea industry[17]. Data presented in Fig. 2, show the average water extract contents to be 38.52%, 39.60%, 33.67%, and 42.19% for S-6, P-8, B-2, and S-CTC type- green teas respectively.

      Based on the current findings, all the analyzed green tea samples complied with the ISO requirement with regard to WE content, implying the presence of adequate extractable substances. However, significant variation was observed between orthodox and CTC type green tea samples. The WE content was higher in case of S-6, 2-CTC (42.19%) and lower in B-2 type processed orthodox green teas (33.67%). It has been reported that the water extract of tea depends on tea and water ratio, temperature of the tea brew, type, and size of made tea particles[34]. Our findings emphasized that the CTC cut facilitated smaller particle size thereby presenting a larger surface area of tea granules exposed to water and enabling effective extraction of soluble constituents in water during brewing as compared to the orthodox tea type, whereas, the soluble solid content of B-2 process was lower compared to other fixing methods which can be attributed to the draining-out of water-soluble components during the blanching process[35].

      The benefit of CTC-type green teas consisting of fannings and dust grades is that these are readily packaged in tea bags for easy marketability and a lesser time is required for brewing out the extractable bioactive compounds, than the leafy orthodox green teas, however, the smaller-sized particles of CTC green teas are more influenced by oxidative processes during storage than whole tea leaves, because a larger surface area is exposed to oxygen and light[7].

      The TQS of steamed (S-6) and pan-fired green teas (P-8) showed significant differences with blanched (B-2) and steamed-CTC (S-CTC) type with lesser bitterness components in orthodox green tea liquor than CTC type (Fig. 3), that indicates the preference of tea tasters towards conventionally processed orthodox type green teas[11,13]. Representative pictures of dry leaf, infused leaf and liquor appearance of green teas processed differently are shown in Fig. 4.

      Figure 3. 

      Taster Quality Score (TQS) of green tea samples processed by different methods. Values are represented as mean ± SE. Different lowercase letters on top of the bars indicate significant difference by ANOVA with Duncan multiple test range at p < 0.05; TQS, Tasters' Quality Scores. S-6, steam-roasting for 6 min; P-8, pan-firing for 8 min; B-2, blanching for 2 min; S-CTC, steam-roasting for 2 min followed by two CTC cuts.

      Figure 4. 

      Representative pictures of dry leaf appearance, infused leaf and liquor colour of green tea processed by different processing methods, used for organoleptic evaluation.

    • The antioxidant activity serves as an indicator of the proportion of antioxidant substances in green tea. Since it is not always possible to characterize the antioxidant potential of tea by a single assay because the majority of naturally occurring antioxidants found in tea have multiple functions, hence, we used the DPPH and FRAP assays in the current study to describe the antioxidant activity of green tea samples processed in different ways. Under the conditions described in this manuscript, no significant differences were observed in the IC50 values of green tea samples processed by different methods (Fig. 5).

      Figure 5. 

      Anti-oxidant activity in terms of DPPH and FRAP assay values of green tea samples processed by different methods. Values are represented as mean ± SE. Different lowercase letters on top of the bars indicate significant difference by ANOVA with Duncan multiple test range at p < 0.05; DPPH, 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical-scavenging ability; FRAP, Ferric reducing antioxidant power; S-6, steam-roasting for 6 min; P-8, pan-firing for 8 min; B-2, blanching for 2 min; S-CTC, steam-roasting for 2 min followed by two CTC cuts.

      The B-2 and P-8 type processed green teas exhibited the maximum and minimum IC50 value of 18.21 and 16.34 μg/ml respectively in the DPPH assay, which may be attributed to the loss of water-soluble antioxidants during blanching and negligible loss during deactivation by dry heat application or pan-firing. Likewise, in the FRAP assay, the values of S-6 and P-8 green teas were significantly higher than in B-2 and S-CTC methods, wherein, the variance noted in the FRAP values can primarily be attributed to the loss of anti-oxidative polyphenols during the blanching and CTC steps of green tea processing[23].

    • Pearson correlation was used to evaluate the relationship among the various chemical quality parameters and tasting scores for the green teas processed by four different methods (Table 2), wherein, a strong positively significant correlation was obtained between EGC and EC, TC and also between C and ECG, TFC. Additionally, caffeine content was positively and significantly correlated with TPC, WE, TQS and likewise, TFC with EC; TC with EGCG; TQS with ECG, WE also displayed significant positive correlation. However, a negative correlation was observed between EGC and C, ECG, WE, TQS; C and EGCG, TC; EC, ECG with EGCG; TC with ECC, TFC, WE, TQS as reported earlier[36]. These results confirm the above discussed results that some of the green tea chemical constituents are correlated to the different methods of green tea processing.

      Table 2.  Correlations between gallic acid (GA), epigallocatechin (EGC), catechin (C), caffeine (CFF), epicatechin (EC), epigallocatechin gallate (EGCG), epicatechin gallate (ECG), total catechin (TC), total polyphenol content (TPC), total flavonoid content (TFC), water extract (WE) and tasters' quality score (TQS) in green tea samples processed by different methods.

      GA EGC C CAFF EC EGCG ECG TC TPC TFC WE TQS
      GA 1
      EGC 0.018 1
      C 0.099 −0.529** 1
      CAFF 0.090 −0.170 −0.118 1
      EC 0.035 0.510** 0.073 −0.186 1
      EGCG −0.021 0.093 −0.669** 0.269* −0.514** 1
      ECG 0.030 −0.679** 0.767** −0.100 −0.044 −0.430** 1
      TC 0.021 0.523** −0.630** 0.084 −0.051 0.809** −0.409** 1
      TPC −0.167 −0.073 −0.067 0.514** −0.088 0.175 0.035 0.137 1
      TFC 0.158 0.241* 0.437** −0.034 0.612** −0.755** 0.147 −0.443** −0.097 1
      WE 0.141 −0.495** 0.273* 0.514** −0.072 −0.326* 0.302* −0.556** 0.149 0.272* 1
      TQS 0.126 −0.483** 0.243* 0.399** −0.079 −0.216 0.364** −0.400** 0.173 0.137 0.856** 1
      **, Correlation is significant at the 0.01 level (1-tailed). *, Correlation is significant at the 0.05 level (1-tailed). GA, gallic acid; EGC, (−)-epigallocatechin; C, (+)-catechin; CAFF, caffeine; EC, (−)-epicatechin; EGCG, (−)-epigallocatechin gallate; ECG, (−)-epicatechin gallate; TC, total catechins; TPC, total polyphenol content; FC, flavonoid content; WE, eater extract; TQS, Tasters' Quality Score. The direction and magnitude of correlation between variables was quantified by the correlation coefficient r. One-tailed p value: *, p < 0.05; **, p < 0.01.
    • The findings of the current study provide practical information about the role of different processing methodologies on green tea quality, and the composition of health-promoting constituents in green tea extract and also establish a trend in which the level of these green tea biochemicals is governed. The phytochemicals and antioxidative properties of orthodox green teas were significantly higher than the CTC type. It is reported that the blanching method of deactivation results in the production of green tea with a significantly lesser amount of caffeine compared to steaming and pan-firing methods. Moreover, a significant increase in the content of water extract was observed in CTC-green tea compared to the orthodox type. However, the organoleptic evaluation by tasters preferred the orthodox green teas processed by steam and pan-firing to blanched and CTC-green teas. The detailed scientific and comparative study on the variation of chemical constituents due to processing differences of green tea provides relevant information for consumers and professionals from the tea and pharmaceutical industry. Further work on calibration of the green tea process parameters to obtain desirable biochemicals of therapeutic value, under large-scale settings, can be attempted.

    • The authors confirm contribution to the paper as follows: Adhikary B and Kashyap B contributed equally to this work. Conceptualization, data curation, writing - original draft: Adhikary B, Kashyap B; funding acquisition: Adhikary B, Kashyap B, Babu A; project administration, Supervision: Adhikary B, Varghese S, Babu A; investigation, validation: Kashyap B, Gogoi RC; resources: Adhikary B, Kanrar B, Babu A; methodology: Kashyap B, Kanrar B; formal analysis: Kashyap B; writing - review & editing: Adhikary B, Kashyap B, Kanrar B, Gogoi RC, Varghese S, Babu A. All authors reviewed and approved the final manuscript.

    • All data analyzed during this study are included in the published article and its electronic supplementary information files.

      • This work was supported by a research grant from the Department of Science and Technology and Biotechnology- Government of West Bengal vide Research Grant, Ref: 936 (Sanc.) ST/P/S&T/1G-18/2016 dated 10/01/2017.

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

      • # Authors contributed equally: Biplab Adhikary, Bishwapran Kashyap

      • Supplemental Table S1 Standard calibration curve equation and R2 (coefficient of determination) values used for analysis of biochemical parameters.
      • Supplemental Fig. S1 Graphical abstract.
      • Supplemental Fig. S2 HPLC chromatograms of mixed standard solution and green tea extracts processed by different methods.
      • Copyright: © 2024 by the author(s). Published by Maximum Academic Press, Fayetteville, GA. 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 (36)
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    Adhikary B, Kashyap B, Kanrar B, Gogoi RC, Varghese S, et al. 2024. Comparative evaluation of the impact of processing methods in determining the levels of health promoting chemical constituents and quality of green tea. Beverage Plant Research 4: e027 doi: 10.48130/bpr-0024-0016
    Adhikary B, Kashyap B, Kanrar B, Gogoi RC, Varghese S, et al. 2024. Comparative evaluation of the impact of processing methods in determining the levels of health promoting chemical constituents and quality of green tea. Beverage Plant Research 4: e027 doi: 10.48130/bpr-0024-0016

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