research paper on stevia plant

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Stevia, Nature’s Zero-Calorie Sustainable Sweetener

Stevia is a plant native to South America that has been used as a sweetener for hundreds of years. Today, zero-calorie stevia, as high-purity stevia leaf extract, is being used globally to reduce energy and added sugar content in foods and beverages. This article introduces stevia, explaining its sustainable production, metabolism in the body, safety assessment, and use in foods and drinks to assist with energy reduction. The article also summarizes current thinking of the evidence for the role of nonnutritive sweeteners in energy reduction. Overall, stevia shows promise as a new tool to help achieve weight management goals.

WHERE DOES STEVIA COME FROM?

Stevia is a naturally sourced, zero-calorie sweetener that has been used as a natural sugar substitute and flavoring ingredient for hundreds of years. The stevia plant is native to South America and was first consumed there over 200 years ago when the indigenous people used leaves of the plant to sweeten beverages or chewed them for their sweet taste. The plant leaves, often called “sweet herb,” were dried and used to sweeten teas and medicines or simply chewed as a sweet treat.

The stevia plant was first scientifically recorded in 1899 as Eupatorium rebaudianum by Moises Santiago de Bertoni, in Paraguay. In 1905, it was later defined as Stevia rebaudiana , a member of the sunflower (Asteraceae) family.

Stevia, as a plant extract, was first commercially adopted as a sweetener by Japan in the 1970s, where it is still a popular ingredient today. Stevia is cultivated mostly in Paraguay, Kenya, China, and the United States and within many other parts of the world, including Vietnam, Brazil, India, Argentina, and Colombia.

Stevia Definitions

Stevia is the generic term used to refer to different forms of the sweetener, including the whole plant Stevia ( S rebaudiana Bertoni) and the leaves where the sweet compounds are found. Stevia extract is a generic name for a preparation made by steeping the leaves of the Stevia plant to extract the sweet compounds from the leaf material.

On the other hand, high-purity stevia leaf extract contains 95% or greater steviol glycosides. Only high-purity stevia extracts meeting this specification are approved by major regulatory agencies, including the Joint Food and Agriculture Organization/World Health Organization (WHO) Expert Committee on Food Additives and Codex Alimentarius (Codex) for use in foods and beverages.

The term “stevia” as used in this article refers to high-purity stevia leaf extract.

Stevia is a sweetener and a natural origin plant extract that has been consumed for over 200 years. However, high-purity stevia leaf extract is now on the market today.

STEVIA’S SWEETNESS

The sweet-tasting components of stevia are called steviol glycosides, which are naturally present in the stevia leaf. There are 11 major steviol glycosides (Figure ​ (Figure1), 1 ), of which rebaudioside A and stevioside are the most abundant. Figure ​ Figure2 2 shows the basic chemical structure of all steviol glycosides. Purified stevia leaf extracts can contain one steviol glycoside or several different glycosides, which can be up to 250 to 300 times sweeter than sucrose. 1

The 11 major steviol glycosides in the stevia plant.

The chemical structure of the steviol backbone for steviol glycosides found in the stevia plant. The “R” structures indicate placement of the various glycoside molecules, which results in the variety of steviol glycosides present in the leaf.

STEVIA PRODUCTION

Figure ​ Figure3 3 illustrates the process used to extract steviol glycosides from the stevia leaf and shows how they are filtered and purified. 2

The processing steps used to obtain high-purity stevia leaf extract from the stevia plant.

The process of purifying stevia into high-purity stevia leaf extract is similar to how other plant-based ingredients, such as cane sugar or natural vanilla extract, are made through a series of steps beginning with the harvested, raw plant material through to the end product. The process begins by drying the leaves and then steeping them in hot water. Next, the liquid extract is filtered and purified with water or in some cases in combination with food-grade alcohol. If food-grade alcohol is used, it is later removed and no significant amount of alcohol remains in the end product. Other processes may be used in some cases. Further technical details are available in the cited article by Prakash et al. 3

The purified steviol glycosides are the same molecules as originally found in the leaf. High-purity stevia leaf extracts (>95% steviol glycosides) are required to meet US and European regulatory approvals and safety standards for foods and beverage use.

SUSTAINABILITY

Stevia requires lower inputs of land, water, and energy to produce the same amount of sweetness found in other natural sweeteners. A carbon and water footprint assessment from one of the largest stevia producers, using sweetness equivalence for comparison, found an 82% reduction in carbon footprint for stevia compared with beet sugar and a 64% reduction compared with cane sugar. The water footprint for stevia was 92% lower than beet sugar and 95% lower than cane sugar ( www.purecircle.com ). The carbon footprint was calculated following Publically Available Standard 2050 (PAS 2050)—the foremost methodology for product lifecycle analysis of carbon emissions that contribute to greenhouse gases. This method incorporated embedded carbon in the agricultural inputs and ingredients used in the processes as well as all direct emissions from operations and transportation of goods, emissions from purchased electricity, and emissions from sources not owned or controlled by company, but only directly related to the supply chain. Water footprint calculation followed the Water Footprint Assessment Methodology as set out by the Water Footprint Network and incorporated green (rain) and blue (irrigation or process) water that went into stevia production.

In addition, stevia is creating opportunities for farmers in countries such as Kenya, Paraguay, and Brazil to grow profitable crops that support public health goals.

PURIFIED STEVIA LEAF EXTRACT

High-purity stevia extract contains 95% or greater steviol glycoside content and is often referred to as stevia, steviol glycosides, stevia extracts, purified stevia leaf extract, high-purity stevia, or rebiana. Only high-purity stevia extracts meeting this specification are approved by major regulatory agencies, including the Joint Food and Agriculture Organization/WHO Expert Committee on Food Additives 4 and Codex, for use in foods and beverages. For simplicity, the term “stevia” as used in this article refers to purified steviol glycosides.

Stevia in Your Foods and Drinks

Food scientists continue to explore ways to use stevia-based sweeteners. Proposed uses for high-purity stevia leaf extracts include soft drinks, canned fruit and jams, ice cream and other dairy products, cakes and desserts, and alcoholic beverages.

Stevia Metabolism

The backbone of all steviol glycosides is steviol, to which various glycoside (glucose) groups attach to form the variety of sweet compounds in stevia (Figure ​ (Figure2). 2 ). Steviol glycosides pass through the upper gastrointestinal tract fully intact. Gut bacteria in the colon hydrolyze steviol glycosides into steviol by snipping off their glucose units. Steviol is then absorbed via the portal vein and primarily metabolized by the liver, forming steviol glucuronide, which is primarily excreted in the urine. Research shows that there is no accumulation of stevia (or any component or by-product of stevia) in the body and that it passes through the body during metabolism. Energy from fermentation of glucose units (usually assessed as 2 kcal/g) is so low that it is minimal, and so, effectively, stevia can be said to provide zero calories. 5 , 6

High-purify stevia leaf extract is not metabolized, so it provides zero calories.

Stevia Safety

The Acceptable Daily Intake (ADI) is the amount of a substance that people can consume in food or beverages on a daily basis during their whole life without any appreciable risk to health. Several regulatory authorities have rigorously evaluated more than 200 peer-reviewed studies on animals and humans examining the safety of high-purity steviol glycosides. Based on this evidence, JECFA has established an ADI that applies to adults and children. The ADI is expressed as steviol equivalents of 4 mg/kg of body weight per day. 7 This equates to approximately 12 mg of high-purity stevia extracts/kg of body weight per day, using a conversion factor of 0.33. This ADI was established using a safety factor of 100, which includes a 10-times factor to account for potential differences between humans and animal species used in toxicological testing and a 10-times factor to account for potential differences within the human population, such as between children and adults. Thus, any potential increased susceptibility of children compared with adults to steviol glycosides has been addressed in the establishment of the ADI. For example, to put the ADI for high purity steviol glycosides into perspective, a 150-lb (70-kg) person would need to consume approximately 40 packets of a table top stevia sweetener that contain 21 mg steviol glycosides per packet daily for a lifetime to maximize the current ADI. Here is the calculation: A 70-kg person consuming the ADI (12 mg/kg per day) would consume 70 × 12 = 840 mg steviol glycosides per day. If a tabletop packet contained about 21 mg steviol glycosides, this person would need to consume 840 / 21 = 40 small tabletop packets per day to maximize the current ADI.

In the United States, high-purity stevia leaf extracts are considered GRAS (generally recognized as safe) by the US Food and Drug Administration. For more information about the Food and Drug Administration GRAS process, see http://www.ncbi.nlm.nih.gov/pubmed/18983884 . There are many ways of producing purified steviol glycosides, and there are many GRAS notices.

Stevia has been shown to be safe in more than 200 studies, and JECFA has established an ADI of 4 mg/kg body weight per day, expressed as steviol equivalents, to guarantee this safety to consumers.

Role of Stevia in Energy Reduction and Weight Management

To fully discuss this issue, there are 4 distinct questions that need to be answered:

• 1. Does sugar contribute to greater energy intake and overweight and obesity?
• 2. Do sugar-sweetened beverages (SSBs) contribute to greater energy intake and overweight and obesity?
• 3. Does replacement of caloric sweeteners with nonnutritive sweeteners (NNS) facilitate weight loss or weight maintenance by helping reduce energy intake?
• 4. Does replacement of caloric sweeteners with stevia facilitate weight loss or weight maintenance by helping reduce energy intake?

Does Sugar Contribute to Greater Energy Intake and Overweight and Obesity?

The fact that “epidemiological studies do not show a positive association between total sugar intake and obesity” was one of the reasons why a positive European Food Safety Authority opinion was not given in 2011 for NNS reducing obesity. 8 Since that time, an important systematic review and meta-analysis, 9 commissioned by WHO, concluded that “Altering intakes of sugars, or SSB, is associated with changes in body weight (more consistently in adults than in children), which seem to be mediated via changes in energy intake because isoenergetic exchange of sugars with other carbohydrates is not associated with weight change.” Thus sugar does seem to contribute to greater energy intake, but it cannot be said categorically to cause obesity.

Do SSBs Contribute to Greater Energy Intake and Overweight and Obesity?

This question has been hotly debated over recent years, and interesting viewpoints have been expressed on all sides (see Kaiser et al 10 and Hu 11 ). The debate centers around which evidence should be considered (randomized controlled trials [RCTs] and cohort studies or just RCTs?) and how the evidence should be interpreted for policy purposes.

The most recent systematic review to address question 2 included 15 prospective studies and 5 RCTs in children and 7 cohort studies and 5 trials in adults. It concluded that SSB consumption promotes weight gain in children and adults. 12 The 15 RCTs in children showed reductions in body mass index gain when NNS were used to replace SSBs, and these benefits were more pronounced in overweight children compared with normal-weight children. The effects were even greater than those achieved with school-based education programs. The greatest effects were seen in the two most recent trials where great care had been taken to conceal the identity of the NNS sweetened drinks. 13 , 14 In one trial, 13 sugar was replaced with sucralose and acesulfame potassium and in the other SSBs was replaced with “diet drinks” with the sweetener not stated. 14 However, it should be noted that the latter trial found an effect after 1 year, but not 2 years, which was the primary outcome identified. In fact, a previous study by these authors found an effect only in the most overweight boys. 15

Does Replacement of Caloric Sweeteners With NNS Facilitate Weight Loss or Weight Maintenance by Helping Reduce Energy Intake?

In 2006, we published a systematic review and meta-analysis to look at the evidence for the effect of NNS, mainly aspartame, on weight loss, weight maintenance, and energy intakes in adults. It addressed the question of how much energy is compensated for and whether the use of sweetened foods and drinks is an effective way to lose weight. 16 We demonstrated that using foods and drinks sweetened with NNS, instead of sucrose, results in a significant reduction in both energy intakes (about 10%) and body weight; the estimated rate of weight loss was about 0.2 kg/wk. Some compensation for the substituted energy does occur, but this is only about one-third of the energy replaced and is probably less when using soft drinks sweetened with NNS because of the smaller compensation usually found for liquids as opposed to foods. However, these results and the compensation values were derived from short-term studies, and more data were needed over the longer term to determine whether a tolerance to the effects of NNS is acquired.

Some progress was made when studies on overweight subjects were separated from those on normal-weight subjects. 17 In this case, the 6 pertinent studies taken altogether showed no overall benefit. However, when the 3 studies performed in overweight subjects were looked at separately, these authors reported a significant benefit on body mass index by replacing sugar with NNS.

However, we still urgently needed a systematic review and meta-analysis of good-quality longer-term recent studies to specifically address question 3: “Does replacement of caloric sweeteners with NNS facilitate weight loss or weight maintenance by helping reduce energy intake?” This was provided in mid-2014. 18 These authors concluded that data from 15 RCTs, which provide the highest quality of evidence for examining the potentially causal effects of NNS intake, indicated that substituting NNS options for their regular-calorie versions results in a modest weight loss and may be a useful dietary tool to improve compliance with weight loss or weight maintenance plans.

Does Replacement of Caloric Sweeteners With Stevia Facilitate Weight Loss or Weight Maintenance by Helping Reduce Energy Intake?

Although there have been many studies on stevia that have produced results confirming the safety of stevia, and there is evidence that stevia does not affect satiety, 19 no long-term trials have been reported that look at the effectiveness of stevia in weight control. However, as reported above, many studies and overviews have been published that report trials undertaken with other NNS, mainly aspartame. We have no reason to believe that the effectiveness of stevia replacing sugar in drinks and foods would lead to different conclusions. More research in humans will be important to clarify the role of stevia in long-term energy reduction.

We need studies to confirm the role of stevia in long-term weight reduction and maintenance.

Stevia is a natural-origin sweetener that is increasing the options for reduced sugar and reduced energy foods and beverages. Stevia shows promise as a tool to help lower energy intakes, which may lead to the reduction and prevention of obesity.

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• Published: 01 June 2021

The chromosome-level Stevia genome provides insights into steviol glycoside biosynthesis

• Xiaoyang Xu 1   na1 ,
• Haiyan Yuan 1   na1 ,
• Xiaqing Yu   ORCID: orcid.org/0000-0002-4545-4781 2 ,
• Suzhen Huang 1 ,
• Yuming Sun 1 ,
• Ting Zhang 1 ,
• Qingquan Liu 1 ,
• Haiying Tong 1 ,
• Yongxia Zhang 1 ,
• Yinjie Wang 1 ,
• Chunxiao Liu 3 ,
• Menglan Hou 1 &
• Yongheng Yang 1  

Horticulture Research volume  8 , Article number:  129 ( 2021 ) Cite this article

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Stevia ( Stevia rebaudiana Bertoni) is well known for its very sweet steviol glycosides (SGs) consisting of a common tetracyclic diterpenoid steviol backbone and a variable glycone. Steviol glycosides are 150–300 times sweeter than sucrose and are used as natural zero-calorie sweeteners. However, the most promising compounds are biosynthesized in small amounts. Based on Illumina, PacBio, and Hi-C sequencing, we constructed a chromosome-level assembly of Stevia covering 1416 Mb with a contig N50 value of 616.85 kb and a scaffold N50 value of 106.55 Mb. More than four-fifths of the Stevia genome consisted of repetitive elements. We annotated 44,143 high-confidence protein-coding genes in the high-quality genome. Genome evolution analysis suggested that Stevia and sunflower diverged ~29.4 million years ago (Mya), shortly after the whole-genome duplication (WGD) event (WGD-2, ~32.1 Mya) that occurred in their common ancestor. Comparative genomic analysis revealed that the expanded genes in Stevia were mainly enriched for biosynthesis of specialized metabolites, especially biosynthesis of terpenoid backbones, and for further oxidation and glycosylation of these compounds. We further identified all candidate genes involved in SG biosynthesis. Collectively, our current findings on the Stevia reference genome will be very helpful for dissecting the evolutionary history of Stevia and for discovering novel genes contributing to SG biosynthesis and other important agronomic traits in future breeding programs.

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Introduction.

High-sugar diets are known to cause severe health problems such as obesity and diabetes 1 . Some countries have levied sugar taxes to reduce the consumption of high-calorie sugars, a recommended strategy to reduce sugar consumption by encouraging substitution with zero-calorie sweeteners 2 . Steviol glycosides, extracted from the leaves of Stevia, contain no calories and have desirable natural sweetness 3 . Stevia rebaudiana (2 n  = 22) is a sweet herb native to Paraguay, and its leaf extract has been used as a natural sweetener for centuries in South America 4 . In addition to sweetness, the two abundant components of SGs, stevioside and rebaudioside A (Reb A), may also provide therapeutic benefits for type 2 diabetes, as these compounds can directly enhance insulin secretion by potentiating TRPM5 channel activity in animal models 5 , 6 . Stevia is widely cultivated in Asia, North America, and Europe for its use as a natural sweetener and traditional medicine.

The genus Stevia belongs to the Eupatorieae tribe within the Asteraceae family. Among the ~230 species of the genus Stevia , S. rebaudiana is the only one that contains SGs 3 , 7 . SGs have a core diterpenoid steviol backbone (aglycone) decorated with different glycosylation patterns at the C-13 and C-19 positions 3 , 8 . These diterpenoid glycosides occur almost exclusively in Stevia leaves, accounting for up to ~20% of the dry weight 9 , 10 . Stevioside and Reb A are the two main components of SGs, followed by Reb C, Reb F, dulcoside A, Reb D, and Reb M. Labeling experiments have revealed that the backbone of SGs is biosynthesized from 5-carbon isoprenoid units, which are predominantly derived from the methylerythritol phosphate (MEP) pathway 11 . The biosynthetic pathways of SG and gibberellic acid (GA) share four steps, and the last common substrate of these two labdane-type diterpenoids is ent -kaurenoic acid 12 , 13 , 14 . In the SG biosynthesis pathway, ent -kaurenoic acid hydroxylase ( ent -KAH) catalyzes the 13-hydroxylation of ent -kaurenoic acid to form ent -13-hydroxy kaurenoic acid (steviol), which serves as the backbone for all SGs 14 , 15 . Then, a series of glycosylation processes of the aglycone (steviol) catalyzed by a set of cytosolic UDP-dependent glycosyltransferases (UGTs) leads to production of diverse types of SGs. Glucose is a major sugar moiety in all SGs, while rhamnose and xylose are present in only a few SGs, such as Reb C and dulcoside A 3 .

Stevia is unique in its accumulation of SGs, which are secondary metabolites of diterpenoids and have initial biosynthetic steps similar to those of GAs. GAs are essential for normal plant growth and development, and genes involved in the GA biosynthesis pathway are conserved and strictly regulated in higher plants 16 , 17 . It seems that the biosynthesis of SGs and GAs should be spatially or temporally separated to avoid disturbing the normal metabolism of GAs 12 ; however, the evolution of SG accumulation and the separation mechanisms of SG and GA biosynthesis in Stevia remain elusive. After the formation of the core tetracyclic diterpenes (GA 12 and steviol), oxidation and glycosylation take place to yield the final bioactive compounds: GAs and SGs, respectively. Unlike the oxidase genes involved in GA biosynthesis, UGT genes participating in diterpenoid glycosylation have rarely been documented 18 , 19 . Stevia is an ideal plant model for the study of diterpenoid glycosylation, not only because its leaves accumulate more than 30 types of SGs but also because of its short growth cycle and easy reproduction. Due to the absence of the genome sequence of Stevia, most studies identifying UGT genes involved in glycosylation of SGs have been based on expressed sequence tags or transcriptomic sequences, and only three UGTs have been characterized to contribute to the biosynthesis of SGs so far 20 , 21 . This deficiency has hindered research on SG biosynthesis and, consequently, has hindered comprehensive understanding of the evolution of Stevia in Asteraceae.

In the present study, we generated a high-quality reference genome sequence for Stevia (cv. ‘Zhongshan No. 7’) through a combination of PacBio sequencing and Hi-C approaches. Based on this genome sequence, we performed an evolutionary analysis of Stevia in the Asteraceae family. Furthermore, candidate gene sets involved in SG biosynthesis were identified. This reference genome will be very helpful for the evolutionary understanding of SG biosynthesis and for quality improvement of Stevia in the future.

Genome sequencing and assembly

The leaves of the Chinese Stevia cultivar ‘Zhongshan No. 7’ were collected for de novo genome sequencing and assembly. Based on K-mer analysis, we estimated a genome size of 1.16 Gb for Stevia, with heterozygosity rates of 0.43% and 73.13% repeats (Supplementary Table 1 and Supplementary Fig. 1 ). To accurately assemble this complex genome with a high rate of repeat sequences, we used a combination of short-read Illumina sequencing, long-read PacBio sequencing, and Hi-C sequence approaches. We obtained 114.96 Gb of PacBio sequencing subreads, providing ~99.5-fold coverage of the Stevia genome (Supplementary Table 2 ). These subreads were assembled into a 1405 Mb genome that contained 6978 contigs, with a contig N50 value of 616.85 kb, and the longest contig was 26.27 Mb in length (Supplementary Table 3 ). A total of 76.86 Gb of Hi-C clean data were generated, of which 90.42% reads were mapped to the assembled contigs (Supplementary Table 4 ). Under the guidance of the Hi-C data, we successfully clustered 6358 contigs into 11 pseudochromosomes and oriented 91.28% of the assembly according to a hierarchical clustering strategy 22 (Supplementary Table 5 and Supplementary Fig. 2 ). The final chromosome-level Stevia assembly was 1416 Mb in length, with an N50 scaffold size of 106.55 Mb (Table 1 ).

We used a combination of three data sources to assess the completeness of the Stevia genome assembly. First, we aligned our Illumina data to the assembled genome, and 98.14% of the clean reads were mapped (Supplementary Table 6 ). A total of 451 of the 458 core eukaryotic genes (CEGs) were identified in our current Stevia genome assembly (Supplementary Table 7 ). Moreover, BUSCO 23 analysis revealed that 86.04% of the complete BUSCOs were present in the Stevia assembly (Supplementary Table 8 ). All these findings suggested that the assembled Stevia genome had high completeness and accuracy.

Annotation of the Stevia assembly

We annotated the repetitive elements of the Stevia genome through homology-based methods and in silico prediction, and 80.11% of the assembly was determined to be composed of repetitive elements. Among them, retrotransposons accounted for 69.45%, and DNA transposons accounted for 5.83%. More than 65% of the Stevia genome consisted of long terminal repeat retrotransposons (LTR-RTs), 32.30% of which belonged to the Copia lineage and 66.76% of which belonged to the Gypsy lineage (Supplementary Table 9 ). It was not surprising that such a high content of LTR-RTs was present in the Stevia genome since LTR-RTs are also present in large proportions in other Asteraceae species, such as Helianthus annuus (sunflower) 24 , Lactuca sativa (lettuce) 25 , and Chrysanthemum nankingense 26 . For protein-coding gene annotation, we used a combination of three methods: homology-based, ab initio, and RNA Seq-assisted prediction methods. Finally, 44,143 protein-coding genes were predicted in our current Stevia assembly, with an average gene length of 3493 bp (Table 1 ). Transcriptome analysis showed that 37,489 predicted genes (84.93%) were supported by at least one of the seven organs (root, stem, and leaves at five different developmental stages). Overall, 41,801 protein-coding genes (94.69%) were assigned functions in at least one of the five databases (NR, TrEMBL, KOG, KEGG, and GO) (Supplementary Table 10 ), and 40,355 were anchored on the 11 pseudochromosomes. Fig. 1b–e shows the Copia density, Gypsy density, gene density, and transcriptional level of each pseudochromosome.

a Circular representation of the pseudomolecules (Mb). b Density of Copia LTR-RTs. c Density of Gypsy LTR-RTs. d Gene density. e Average transcript levels, log 2 (RPKM). f GC content. g Syntenic blocks across Stevia pseudomolecules. RPKM reads per kb per million reads

Evolutionary history of S. rebaudiana

To understand the evolutionary relationship between Stevia and other Asteraceae plants, we performed a comparative genomic analysis using Vitis vinifera , Solanum lycopersicum , Daucus carota , and five Asteraceae plants ( L. sativa , C. nankingense , Artemisia annua , H. annuus , and S. rebaudiana ). Phylogenetic analysis based on 799 single-copy orthologous genes identified in these eight species confirmed the close relationship between Stevia and sunflower (Heliantheae alliance) and between C. nankingense and A. annua (Anthemideae tribe) (Fig. 2a ). The estimated divergence time of Stevia and sunflower was ~28–31 million years ago (Mya). The most recent common ancestor (MRCA) of Stevia and sunflower diverged from the MRCA of C. nankingense and A. annua ~37–38 Mya, which is consistent with the findings of Song et al. 26 . The MRCA of Stevia and C. nankingense diverged from lettuce ~39–40 Mya (Fig. 2a ).

a Phylogenetic tree of Stevia and seven other plants based on 799 single-copy orthologous genes. b Ks distributions. Left y -axis, Stevia-sunflower orthologues (blue), Stevia-lettuce orthologues (orange); right y -axis, Stevia paralogues (green), sunflower paralogues (dark green), lettuce paralogues (purple). c Synteny blocks of Stevia-lettuce-sunflower

We further investigated whole-genome duplication (WGD) events during Stevia evolution since WGD has been considered a significant source of plant genetic, biochemical, and evolutionary novelty 27 , 28 , 29 . We identified 5209 paralogous gene pairs that accounted for 20.69% of the predicted Stevia genes using the MCScanX package 30 . The Ks distribution of these duplicated gene pairs peaked at 0.53, reflecting the occurrence of a WGD event ~32.1 Mya (Fig. 2b ). Based on the Ks distribution of the orthologous gene pairs between Stevia and sunflower, we estimated that their divergence time was ~29.4 Mya, indicating that they diverged soon after the WGD event (WGD-2) experienced by their common ancestor 24 . The Ks distribution of homologous gene pairs clearly illustrated that whole-genome triplication (WGT-1, ~45.5–51.5 Mya) occurred in lettuce (Fig. 2b ), which is also believed to have occurred in the ancestry of most Asteraceae 24 , 25 , 26 , 31 . This analysis showed that Stevia experienced a complicated evolutionary history characterized by a recent WGD-2 shared with sunflower, the basal WGT-1 in Asteraceae, and the ancestral paleohexaploidy event (WGT-γ) that occurred in all eudicots 32 . Thus, for any ancestral region from the MRCA of Asteraceae (post-WGT-1), two inherited regions are currently expected to exist in the Stevia and sunflower genomes compared to the lettuce genome (Fig. 2c ). Although Stevia and sunflower experienced the same paleopolyploidy events (WGT-γ, WGT-1, and WGD-2) and there were many collinear regions between their genomes (Supplementary Fig. 3 ), these two species may have undergone different chromosome rearrangement patterns and duplicated gene loss after divergence, resulting in different chromosome numbers and genome sizes.

Gene family analysis

Based on sequence homology, a total of 41,701 gene families containing 276,277 genes were identified using the predicted genes of the above eight plants (seven from asterids and V. vinifera as an outgroup) (Fig. 3a and Supplementary Table 11 ). Of these, 5749 gene families consisting of 68,964 genes were shared among all eight plants, and 12,326 were shared among the five Asteraceae plants (Fig. 3b ). We assigned 40,214 Stevia genes to 20,147 families and found that 1057 gene families contained 4281 genes unique to Stevia. Gene Ontology (GO) enrichment analysis revealed that these unique gene families were mostly involved in RNA-directed DNA polymerase activity (GO:0003964), aspartic-type endopeptidase activity (GO:0004190), and RNA binding (GO:0003723) (Supplementary Fig. 4 ).

a The red and blue numbers mapped to the species phylogenetic tree indicate gene families that underwent expansion and contraction, respectively. b Venn diagram of shared gene families in Stevia and four other plants of Asteraceae. c Phylogenetic tree of the terpene synthase (TPS) gene family in Stevia. The TPS subfamilies are labeled

Further gene family analysis demonstrated that 323 gene families were expanded in the Stevia genome, while 346 were contracted (Fig. 3a ). GO enrichment analysis of the expanded gene families of Stevia revealed that they were enriched for transferase activity (GO:0016758), monooxygenase activity (GO:0004497), ADP binding (GO:0043531), catalytic activity (GO:0003824), and terpene synthase activity (GO:0010333) (Supplementary Fig. 5 ). KEGG enrichment analysis revealed that the expanded gene families of Stevia were enriched mainly for phenylpropanoid biosynthesis (ko00940), terpenoid backbone biosynthesis (ko00900), flavonoid biosynthesis (ko00941), monoterpenoid biosynthesis (ko00902), cyanoamino acid metabolism (ko00460), and sesquiterpenoid and triterpenoid biosynthesis (ko00909) (Supplementary Fig. 6 ). The GO and KEGG enrichment analyses demonstrated that a considerable number of these expanded gene families participated in the biosynthesis of specialized metabolites. As the terpenoid biosynthesis pathway was enriched several times, we further investigated the expansion pattern of the terpene synthase (TPS) gene family, which drives the diversification of terpenoids. Eighty-two TPS genes were identified in the Stevia genome, which could be divided into five subfamilies. More than three-quarters of the Stevia TPS genes were classified into the TPS-a and TPS-b subfamilies, indicating significant expansion of these two subfamilies (Fig. 3c ).

Genes involved in SG biosynthesis

Accumulation of large amounts of SGs in leaves is the most notable feature of Stevia. Although the SG biosynthetic pathway has been extensively studied during the past two decades, and although some of the critical UGT genes have been well characterized 21 , 33 , we obtained new insights into SG biosynthesis by combining genomic and transcriptome analyses. All terpenes are derived from 5-carbon isoprenoid units produced through either the MEP pathway or the mevalonate (MVA) pathway 34 . Candidate genes in the MEP and MVA pathways were identified using homolog searching and functional annotation methods. Transcriptome analysis revealed that almost all the candidate genes in the MEP pathway were expressed in seven selected tissues, including leaves at different developmental stages, with high accumulation of SGs (Fig. 4 ). However, the expression levels of HMGR and MK in the MVA pathway were deficient in the leaves, indicating that the 5-carbon isoprenoid unit for SG biosynthesis comes from mainly the MEP pathway instead of the MVA pathway, which is consistent with the conclusions derived from the results of labeling experiments 11 .

a Diagram depicting the pathway of SGs biosynthesis. Inside the dashed box is the unique SGs biosynthesis pathway in Stevia. b Expression patterns of candidate genes of the SGs biosynthesis pathway. RS root at the seedling stage, SS stem at the seedling stage, LS leaf at the seedling stage, LV leaf at the vegetative stage, LB leaf at the bud stage, LIF leaf at the initial flowering stage, LPF leaf at the peak flowering stage

Since the biosynthesis of SGs shares four steps with the biosynthesis of GAs before the generation of ent -kaurenoic acid, we identified all candidate genes involved in this common pathway, including 14 geranylgeranyl diphosphate (GGPP) synthase (GGPPS) genes, seven en t-copalyl diphosphate synthase ( ent -CPS) genes, five ent -kaurene synthase ( ent -KS) genes, and six ent -kaurene oxidase ( ent -KO) genes (Fig. 4 ). All four types of genes were multicopy genes in the Stevia genome, and the homologous genes showed expression differentiation (Fig. 4b ), reflecting subfunctionalization or neofunctionalization of these duplicated genes. Stevia has evolved to biosynthesize SGs based on the conserved early steps of the GA biosynthesis pathway in vascular plants.

Steviol glycoside biosynthesis diverges from GA biosynthesis with the 13-hydroxylation of ent -kaurenoic acid by ent -KAH. The evolution of ent -KAH from numerous P450s was the key step of SG biosynthesis in Stevia; however, cloning of its encoding gene has not been successful yet 3 , 35 . Several potential ent -KAH genes of Stevia have been deposited in the NCBI database, and most belong to the CYP716 family. In contrast, CYP714A2, a member of the CYP714 family of Arabidopsis thaliana , has been reported to catalyze the 13-hydroxylation of ent -kaurenoic acid when expressed in yeast 36 . Thus, we identified all putative members of the CYP716 and CYP714 families in the Stevia genome. There was significant expansion of CYP716 genes, and four tandemly duplicated genes ( Streb.1G007430 , Streb.1G007460 , Streb.1G007470 , and Streb.1G007480 ) were consistently highly expressed in leaves with SG biosynthesis (Supplementary Fig. 7 ). In contrast, there was only one member of the CYP714 family in the Stevia genome ( Streb.8G019490 ), and it was hardly expressed in the leaves (Fig. 4b ). After the formation of steviol, continuous glycosylation processes catalyzed by a set of UGTs lead to different types of SGs (Fig. 4a ). UGT genes were highly enriched (GO:0016758, P  < 0.001) among the expanded gene families of Stevia. In total, we identified 259 putative UGT genes in the Stevia genome, and 86 UGT genes were expressed in at least two of the five selected leaf tissues (Supplementary Fig. 8 ), including three UGT genes that have been reported to be involved in SG biosynthesis ( UGT85C2 , UGT74G1 , and UGT76G1 ). Unearthing of these candidate UGT genes through genomic and transcriptome analyses will accelerate the identification of UGT genes involved in specific SG glycosylation.

Obesity is a serious global health issue that affects millions of people, with a high-sugar diet being one of the leading causes of obesity. Reducing sugar intake by substitution with zero-calorie sweeteners is an effective way to reduce dietary energy consumption. Although artificial sweeteners such as saccharin, aspartame, and sucralose are widely added to various food products in daily use, long-term uptake of these sugar substitutes may pose health risks 37 , 38 . There is a strong demand for natural zero-calorie sweeteners, and SGs may be the most promising candidates. Steviol glycosides have been approved by the foremost regulatory authorities worldwide for use in foods and beverages. High yields and improvements in the levels of the best-tasting SGs, such as Reb A, Reb D, and Reb M, are currently the main objectives for breeding of Stevia.

Thus far, there have been no comprehensive analyses combining genomic and transcriptomic methods to provide in-depth insights into the unique diterpenes (SGs) of Stevia. It is still very challenging to construct a high-quality Stevia genome assembly based only on second-generation sequencing owing to the large size and high complexity of the genome as well as the percentage of repeats 39 . Here, we propose a chromosome-level genome assembly of Stevia. The Stevia genome spanning 1416 Mb was obtained, with a contig N50 of 616.85 kb and a scaffold N50 of 106.55 Mb. We predicted 44,143 protein-coding genes in our current assembly using homology-based, ab initio, and RNA Seq-assisted prediction methods; this number is almost twice that of the previous genome assembled using second-generation short sequences (24,994), probably because only 411 Mb of the genome had previously been assembled 39 . Therefore, the genome assembled using long sequences and Hi-C approaches in this study is superior to the genome previously assembled using only short sequences.

More than four-fifths of the Stevia genome consisted of repetitive elements, of which 21.02% belonged to the Copia lineage and 43.44% belonged to the Gypsy lineage. In sunflower, more than three-quarters of the genome was composed of LTR-RTs, 59.9% of which belonged to the Gypsy lineage and 25.8% of which belonged to the Copia lineage 24 . In C. nankingense , repetitive elements accounted for 69.6% of the genome, among which LTR-RTs ( Gypsy and Copia ) were the most abundant 26 . Having many repetitive sequences, especially LTR-RTs, might be a significant feature of the Asteraceae family, contributing to the genome sizes of its members.

Comparative genomic analyses of Stevia and other Asteraceae plants have provided crucial clues regarding Stevia genome evolution in Asteraceae. Our results showed that Stevia and sunflower diverged ~29.4 Mya, shortly after the WGD event (WGD-2, ~32.1 Mya) that occurred in their MRCA (Fig. 2a, b ). Stevia, a member of the Asteraceae family, also experienced a basal WGT-1 event in Asteraceae, and a WGT-γ event occurred in all eudicots 24 , 25 , 32 . Most of the syntenic blocks present in the Stevia genome were derived from the recent WGD-2 event, while syntenic blocks derived from ancient WGT-1 events were rarely preserved (Fig. 2b ). After it diverged from an ancestor shared with sunflower, Stevia evolved to synthesize SGs, unique metabolites not found in other plants. The expansion of specific gene families may play important roles in promoting phenotypic diversification as well as in the evolution of novel traits in plants 40 , 41 . The expanded genes in Stevia were mainly enriched for biosynthesis of specialized metabolites, especially biosynthesis of terpenoid backbones, and for further oxidation and glycosylation of these compounds (Supplementary Figs. 5 , 6 ). We further identified all candidate genes in the pathway of SG biosynthesis based on the genome sequences and found that the essential genes responsible for steviol biosynthesis were multiple-copy genes (Fig. 4b ). These duplicated genes might be important contributors to the ability of Stevia to synthesize SGs. Thus, this high-quality chromosome-level genome assembly will undoubtedly benefit researchers in the exploration of Stevia characteristics.

Materials and methods

Leaf collection, dna library construction, and genome sequencing.

Fresh young leaves present during the seedling stage of ‘Zhongshan No. 7’, a cultivated diploid Stevia species, were collected from the Stevia germplasm resource laboratory located at the Nanjing Botanical Garden Mem. Sun Yat-Sen. Genomic DNA was isolated for Illumina and PacBio sequencing. For Illumina sequencing, a short-read (270 bp) library was constructed and sequenced on an Illumina HiSeq platform (Illumina, CA, USA), and 141.90 Gb of clean reads were obtained. For PacBio sequencing, genomic DNA was fragmented to ~20 kb to construct a long-read library according to the manufacturer’s instructions (Pacific Biosciences, CA, USA), and then the library was sequenced on a PacBio Sequel platform. After filtering out the low-quality reads and sequence adapters, we obtained 114.95 Gb of clean subreads with an N50 value of 12.82 kb.

Genome assembly

For de novo genome assembly, we first used Canu (v1.5) 42 to correct for potential errors in the PacBio subreads. Then, the high-quality PacBio subreads were independently assembled using WTDBG (v1.2.8), FALCON (v0.7) 43 and Canu (v1.5). These three assembly strategies yielded 1.36, 3.25, and 2.03 Gb assemblies, and the contig N50 sizes of these three assemblies were 205.51, 59.71, and 277.70 kb, respectively. We further merged the well-assembled WTGDB and Canu assemblies using Quickmerge 44 . To correct the indel and SNP errors in the assembly sequence, we mapped paired-end Illumina reads to the merged assembly using Pilon 45 . Finally, the size of the genome assembled using PacBio long reads was 1.40 Gb with a contig N50 value of 616.85 kb (Supplementary Table 3 ). To evaluate the quality of the assembly, we used BWA 46 to map the short paired-end reads to the optimized contigs and then performed CEGMA 47 and BUSCO 23 analyses.

Chromosome-level assembly

Hi-C sequencing for the chromosome-level genome assembly was performed as previously described 48 . Briefly, fresh young leaves present at the seedling stage of ‘Zhongshan No. 7’ were collected and fixed in formaldehyde solution. Hin dIII was used to digest the chromatin extracted from the fixed leaves. The DNA fragments were then ligated together to form chimeric junctions after biotinylation. Next, the enriched chimeric junctions were physically sheared into DNA fragments of 300–700 bp in length. Biotin-containing DNA fragments were enriched through streptavidin pulldown and then subjected to Illumina HiSeq sequencing. Finally, ~76.86 Gb of clean Hi-C reads were generated.

HiC-Pro 49 was used to assess the Hi-C sequencing data. The Hi-C sequencing data were mapped to assembled contigs using BWA-aln 46 . The preassembled scaffolds were split into 50 kb segments on average and conjoined with unique mapped reads for assembly using LACHESIS software 22 . To evaluate the final chromosome assemblies, we divided them into bins of equal lengths (100 kb) and visualized the interaction matrix in a heat map.

Genome annotation

De novo searches and homology-based alignments were used to predict repetitive sequences across the Stevia genome. We first used PILER-DF (v2.4) 50 , RepeatScout (v1.0.5) 51 , and LTR_FINDER (v1.05) 52 to predict de novo repetitive sequences and classified them into families using PASTEClassifier 53 . We then used RepeatMasker (v4.0.6) 54 to scan the integrated database of the de novo repetitive sequences and the known Repbase 55 TE library.

We used homology-based, ab initio, and RNA Seq-assisted approaches to predict protein-coding genes in the Stevia genome assembly. Augustus 56 , GlimmerHMM 57 , SNAP 58 and GeneID 59 were used for ab initio programs. In homologous predictions, the protein sequences of A. thaliana , H. annuus , L. sativa , and Oryza sativa from Phytozome were downloaded and aligned to the assembled Stevia genome using TBLASTN 60 . We then aligned the homologous genomic sequences against matching proteins to construct the exact protein-coding gene models using GeMoMa 61 . For the RNA Seq-assisted predictions, RNA sequencing reads from different organs of Stevia were mapped to the assembly, and transcripts from these mapping results were identified using GeneMarkS-T 62 and TransDecoder ( https://github.com ). We integrated all gene models obtained from the above three annotation procedures with EVM 63 to construct a final consensus set and then filtered it with PASA (v2.0.2) 64 . These predicted protein-coding genes were then assigned to BLAST against public databases, including TrEMBL 65 and NCBI nonredundant protein databases. Blast2GO 66 was used to determine the functions and pathways based on the GO 67 and KEGG 68 databases.

Genome evolution and gene family analysis

Orthologous groups among the eight plants ( V. vinifera , S. lycopersicum , D. carota , L. sativa , C. nankingense , A. annua , H. annuus , and S. rebaudiana ) were identified using OrthoMCL 69 . All-versus-all comparisons were performed using BLASTP ( E -value: 1e−05), and orthologous groups were clustered using OrthoMCL. We used MAFFT 70 to align the protein sequences of 799 single-copy genes, removed the poorly aligned regions with Gblocks 71 , and concatenated the alignment results for phylogenetic analysis using RAxML (v8.0.0) 72 . We estimated the species divergence times using MCMCTREE (v4.0) within the PAML package 73 . The estimated divergence times for V. vinifera - H. annuus (111–131 Mya), S. lycopersicum - D. carota (95–106 Mya) and L. sativa - A. annua (34–40 Mya) in TimeTree ( http://www.timetree.org ) were used to calibrate the tree. The expansion and contraction of the gene families clustered by OrthoMCL in the eight plants were determined with CAFÉ (v4.2) 74 .

WGD analysis

All-versus-all protein sequence comparisons were performed using BLASTP ( E -value: 1e−05) to identify homologous gene pairs. Syntenic blocks within and between species were determined using MCScanX 30 . The Perl script ‘add_ka_and_ks_to_collinearity.pl’. implemented in the MCScanX package was used to calculate the Ks values of the collinear homologous gene pairs. For five Asteraceae species, the neutral substitution rate of asterids ( r  = 8.25E−9) was applied to calculate the divergence date of the WGD or speciation events 24 . A Stevia-lettuce-sunflower syntenic block diagram and dot plot of coding genes between Stevia and sunflower were drawn with TBtools 75 . An image of the syntenic blocks and genomic features in the Stevia genome was produced with Circos (v0.69) 76 .

Data availability

The Illumina short reads and PacBio long reads have been deposited in the NCBI SRA database under BioProject ID PRJNA684944. The transcriptome data have been deposited in the NCBI SRA database under BioProject ID PRJNA705537. The final chromosome-scale genome assembly and annotation data have been deposited in the Figshare database ( https://doi.org/10.6084/m9.figshare.14169491.v1 ).

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Acknowledgements

The research was supported by the National Natural Science Foundation of China (31701497 and 31601371), the Natural Science Foundation of Jiangsu Province (BK20160600 and BK20180312), and the Jiangsu Key Laboratory for the Research and Utilization of Plant Resources (JSPKLB201801 and JSPKLB201832).

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These authors contributed equally: Xiaoyang Xu, Haiyan Yuan

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Institute of Botany, Jiangsu Province and Chinese Academy of Sciences/Jiangsu Provincial Platform for Conservation and Utilization of Agricultural Germplasm, Nanjing, 210014, Jiangsu, China

Xiaoyang Xu, Haiyan Yuan, Suzhen Huang, Yuming Sun, Ting Zhang, Qingquan Liu, Haiying Tong, Yongxia Zhang, Yinjie Wang, Menglan Hou & Yongheng Yang

College of Horticulture, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China

Institute of Pomology, Jiangsu Academy of Agricultural Sciences/Jiangsu Key Laboratory for Horticultural Crop Genetic Improvement, Nanjing, 210014, Jiangsu, China

Chunxiao Liu

Biomarker Technologies Corporation, Beijing, 101300, China

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X.X., Y.Y., and H.Y. conceived the study; H.T., Y.W., and Y.Z. collected samples; L.W. and X.X. performed the genome sequencing; X.X., X.Y., S.H., Y.S., C.L., T.Z., Q.L., and M.H. performed the data analyses; X.X. and H.Y. wrote the manuscript; and Y.Y. revised the manuscript. All authors read and approved the final manuscript.

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Correspondence to Yongheng Yang .

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Xu, X., Yuan, H., Yu, X. et al. The chromosome-level Stevia genome provides insights into steviol glycoside biosynthesis. Hortic Res 8 , 129 (2021). https://doi.org/10.1038/s41438-021-00565-4

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Received : 23 November 2020

Revised : 07 March 2021

Accepted : 14 March 2021

Published : 01 June 2021

DOI : https://doi.org/10.1038/s41438-021-00565-4

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Stevia (Stevia rebaudiana) a bio-sweetener: a review

Affiliation.

• 1 Department of Agricultural Engineering and Food Technology, S.V.B.P. University of Agriculture & Technology, Meerut, India. [email protected]
• PMID: 19961353
• DOI: 10.3109/09637480903193049

Studies revealed that Stevia has been used throughout the world since ancient times for various purposes; for example, as a sweetener and a medicine. We conducted a systematic literature review to summarize and quantify the past and current evidence for Stevia. We searched relevant papers up to 2007 in various databases. As we know that the leaves of Stevia plants have functional and sensory properties superior to those of many other high-potency sweeteners, Stevia is likely to become a major source of high-potency sweetener for the growing natural food market in the future. Although Stevia can be helpful to anyone, there are certain groups who are more likely to benefit from its remarkable sweetening potential. These include diabetic patients, those interested in decreasing caloric intake, and children. Stevia is a small perennial shrub that has been used for centuries as a bio-sweetener and for other medicinal uses such as to lower blood sugar. Its white crystalline compound (stevioside) is the natural herbal sweetener with no calories and is over 100-300 times sweeter than table sugar.

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Growth and development of stevia cuttings during propagation with hormones in different months of the year.

Graphical Abstract

1. Introduction

2.1. temperatures during the development of the experiment, 2.2. stevia plantlet growth and development 28, 35, 42, and 49 days after establishment (dae), 2.3. growth and development of stevia plantlets in different months of the year, 2.4. effect of hormones on growth and development of stevia plantlets, 3. discussion, 3.1. temperatures during development of the experiments, 3.2. growth and development of stevia plantlets at 28, 35, 42 and 49 dae, 3.3. growth and development of stevia plants in different months of the year, 4. materials and methods, 5. conclusions, author contributions, acknowledgments, conflicts of interest.

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Castañeda-Saucedo, M.C.; Tapia-Campos, E.; Ramírez-Anaya, J.d.P.; Beltrán, J. Growth and Development of Stevia Cuttings During Propagation with Hormones in Different Months of the Year. Plants 2020 , 9 , 294. https://doi.org/10.3390/plants9030294

Castañeda-Saucedo MC, Tapia-Campos E, Ramírez-Anaya JdP, Beltrán J. Growth and Development of Stevia Cuttings During Propagation with Hormones in Different Months of the Year. Plants . 2020; 9(3):294. https://doi.org/10.3390/plants9030294

Castañeda-Saucedo, Ma Claudia, Ernesto Tapia-Campos, Jessica del Pilar Ramírez-Anaya, and Jaqueline Beltrán. 2020. "Growth and Development of Stevia Cuttings During Propagation with Hormones in Different Months of the Year" Plants 9, no. 3: 294. https://doi.org/10.3390/plants9030294

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Are Artificial Sweeteners Safe?

Health concerns have been mounting for decades. Here’s what the research suggests.

By Alice Callahan and Dani Blum

When artificial sweeteners entered the U.S. market in the 1950s, food manufacturers made a big claim: That they could satisfy the American sweet tooth without the negative health effects — and calories — of sugar.

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Systematic Research into a Novel Method of Solar Photovoltaic Power Generation Applied to a Hydropower Plant

19 Pages Posted: 24 Jul 2024 Publication Status: Under Review

Wuchang Wang

China Institute of Water Resources and Hydropower Research (IWHR)

China Institute of Water Resources and Hydropower Research (IWHR) - State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin

State Grid Beijing Electric Power Company

Concerns regarding global climate change have rendered energy conservation and emission reduction (ECER) increasingly important, particularly in traditional power plants. In a power plant, a significant amount of power is consumed by the station service loads used to maintain the normal operation of the units, which results in an increase in energy consumption and even carbon emissions if non-clean energy is utilized. For economical and low-carbon operations, conventional approaches mostly focus on the optimal design of the station service system but fail to eliminate the dependence on traditional power sources. This paper proposes a method for solar photovoltaic power generation in traditional power plants and develops a building-integrated photovoltaic (BIPV) system using solar energy and building resources to facilitate the ECER of power plants. Moreover, an actual hydropower plant is considered as a case study to demonstrate the technical feasibility of this method. The results reveal that the BIPV system could satisfy the annual station service power consumption requirements, and the saved and surplus power could increase the output capacity of the power plant. Therefore, this study provides technical guidance and a theoretical basis for energy-saving designs or renovations in similar power plants.

Keywords: Station service system, Hydropower plant, Energy conservation and emission reduction (ECER), Distributed generation (DG), Building integrated photovoltaic (BIPV).

Suggested Citation: Suggested Citation

Wuchang Wang (Contact Author)

China institute of water resources and hydropower research (iwhr) ( email ), china institute of water resources and hydropower research (iwhr) - state key laboratory of simulation and regulation of water cycle in river basin ( email ), state grid beijing electric power company ( email ), do you have a job opening that you would like to promote on ssrn, paper statistics.