重庆青蒿资源调查、种质筛选及栽培中合理的氮磷钾肥和密度
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摘要
青蒿(Artemisia annua L)为菊科蒿属一年生草本,传统中药,具有清热解暑、除蒸、截疟的作用。其叶片及花蕾提取青蒿素,为目前青蒿素类药物的唯一原料来源。我国学者根据传统中医药,首先从青蒿中提取并自主研制出青蒿素类药物,是四大传染疾病之一——疟疾的唯一特效治疗药物,其高效、速效、安全被世界广泛认可,成为首个被收入世界药典的中药,在世界卫生组织(WHO)推动下,已有超过50个国家和地区将其列为抗疟首选指定用药。
青蒿虽是世界性的广布物种,但仅极少数地区青蒿素含量相对较高,能达到工业提取水平之上。而重庆则是这极少数地区之一。在这极少数地区发展青蒿种植业,可以拯救数以亿计疟疾患者,具有极重大社会意义,而且,有利于将独特资源优势转化为经济优势,也具有极显著经济效益。同时,青蒿素也为传统中药树立形象,对其它中药走向世界具有引领作用。
青蒿种植和青蒿素生产具有如此重要意义,那么,选育高含量品种,以及通过栽培技术提高青蒿素含量和产能,成为我们面临的关键而十分紧迫的课题。特别是青蒿素含量至关重要。基于此,本文以提高青蒿素为研究核心,围绕种质筛选和栽培两个方向,展开4个部分的研究：
1青蒿素含量的测定
(1)测定方法的建立与评价
分别建立紫外分光光度法(UVSPM)和高效液相色谱法(HPLC)测定青蒿素,方法学研究表明两方法操作简便、稳定性高、精度准、重现性好。分别对9个样品两次重复进行测定,结果经t检验,表明两种方法测定青蒿素含量的没有差异(p=0.4527)。
(2)样品的提取
采用(L9(34))正交试验方案,研究提取溶剂、溶剂用量、提取温度和提取时间4因素对提取效果的影响,结果表明：提取温度是最为关键的因素,40℃最佳,低于或高于40℃提取效果都不好；提取溶剂对提取影响显著,宜选石油醚(30-60℃)；提取剂用量(料液比)对提取效果影响极显著,宜选50 mL；提取时长对提取结果影响极显著,宜选2小时。
进一步对比试验表明：超声波可以缩短提取时间或降低提取次数,同时可减少提取溶剂用量；增加取剂用量和缩短提取时间之间,可以很好互相弥补,增加提取次数比延长提取时间更有效。5种组合方案为优选提取方法,它们提取效果好,彼此无差异。
(3)样品采后干燥方法
晒干、40℃烘干效果最佳,阴1天后再晒干或40℃烘干,对结果也没有显著影响；自然风干则含量显著降低；烘干超过40℃后,青蒿素含量则随温度升高而极显著降低。
(4)样品储存
储存时长、温度、样品水分含量和包装4因素对青蒿储存过程中青蒿素含量变化影响都极显著。青蒿素含量随储存时间而降低,但前2个月,趋势总体上相对平稳,之后降幅增大、降速加快；样品水分含量越高青蒿素衰降越快且幅度越大；4℃低温青蒿素衰降比常温平稳；包装的影响则取决于样品的水分含量和温度,低温时：青蒿素含量高低顺序为：纸袋+塑料袋+干燥剂>塑料袋>纸袋,高水分含量、室温时,凡有塑料袋都加速青蒿素衰降。
包装的实际作用是防潮,因此,除时间外,样品储存的最关键因素是样品水分含量和温度,即样品始终要处在低水分含量、低温度条件下。干燥度高(储存前40℃烘干至恒重的样品,水分含量5%-7%),4℃低温条件,储存1年后青蒿素还保有90%左右,采用纸袋+塑料袋+干燥剂的包装,最好效果青蒿素含量可以1年后仍然有95.5%。相反,而湿润环境下的样品风干样(水分含量15%-16%)、室温储存,无论什么包装,长时间储存都会让青蒿变得没有价值,1年后,青蒿素含量最低仅剩不到30%左右。
2重庆青蒿资源及生境调查
分别于2005、2009年共调查重庆148个样品点青蒿及其生境,结果如下：
(1)青蒿品质
全市平均青蒿素含量为5.92g·kg-1,幅度1.09-13.03g·kg-1。
青蒿品质表现很强的地域性的分布特点：渝东南(酉阳)片区含量最高,极显著高于其他3片区,是其它3片区的1.5-2.5倍左右,尤其2005年野生资源。
栽培青蒿品质较野生青蒿有极显著提高,2005、2009年和两年总计全市栽培较野生青蒿素含量分别提高34.5%、24.4%和29.5%,同时栽培也提高了青蒿品质的整齐度。
从时间演变来看,2009年品质较2005年总体上有小幅提高(7.88%)。其中,主城(北碚)、渝东(万州)和渝西(永川)有较大幅度提高或提高趋势；但优质资源地的渝东南(酉阳)则呈相反的变化,野生和栽培青蒿品质都呈下降趋势(野生、栽培和总平分别下降11.1%、8.10%、9.57%)。
(2)生境因子
水文、光照和土壤质地极显著地影响青蒿素含量,土壤类型的影响则很小。水文条件好,青蒿素含量愈高,且变异系数越小,4个水文等级青蒿素含量高低相差2.26倍。光照充足有利于青蒿素含量提高,遮荫则大幅降低青蒿素含量,4个光照等级青蒿素含量高低相差3.3倍。4个质地等级中,最适宜的质地为“偏重”,然后为“偏轻”和“重”,质地“沙”不利于青蒿中的青蒿素。
调查的中的紫色土、水稻土、黄壤3种土壤类型对栽培青蒿的品质没有影响,野生青蒿则水稻土、紫色土显著高于黄壤。
(3)生境土壤养分及与青蒿素含量相关性
土壤有机质、碱解氮、有效磷和速效钾被测定。青蒿素含量与上述土壤养分均极显著正相关。
(4)青蒿素与生境的土壤养分回归数量模型和通径分析
以青蒿素含量为因变量(Y),有机质(X1)、碱解氮(X2)、有效磷(X3)和速效钾(X4)为自变量,分别能较好建立线性逐步回归、二次多项式逐步回归和引入高次及养分比的线性逐步回归方程式,回归系数和通径分析表明,影响青蒿素含量不仅有养分绝对数量和养分间交互作用,养分比例也同样发挥着重要作用。因此,青蒿种植需同时兼顾土壤中的养分数量和养分平衡。
(5)重庆优质青蒿的土壤养分标准与诊断
去掉水文光照条件极端、青蒿素含量居中的样点,剩下分为青蒿素高含量和低含量两个样本群组, t-检验比较土壤养分和养分比例,都存在显著性差异。采用植物营养中养分综合诊断法,以高含量组土壤平均有效氮磷钾及其比例平均值,结合其一定范围的置信限,建立重庆优质青蒿的土壤养分标准,按这一标准进行养分诊断和推荐施肥。
3青蒿种质材料评比与筛选
(1)种质材料间性状差异
50份来源于重庆及周边省份青蒿种质材料,田间试验,在同一肥水、环境和管理条件下,多数不同种质材料间不仅在青蒿素含量、青蒿素单株产量存在极大差异,还在生物量、生物量比重、植株形态、生长期共计21个指标存在极显著差异。巨大的差异,不仅表明青蒿材料间差异大,也更表明青蒿种质资源的丰富,还表明种质材料筛选很必要。
(2)种质材料筛选
①优质种质材料筛选：按青蒿素含量高低,筛选出高含量材料13份,其中,超过9.5 g·kg-1的超优质材料6份,8.5-9.5 g·kg-1的优质材料7份。
②高品质与高产能的复合筛选：按青蒿素含量和单株青蒿素产量,筛选出优质超高产型材料3份(青蒿素含量产量分别8.5-9.5g·kg-1和≥1.5 g·plant-1),超优质高产型材料5份(≥9.5 g·kg-1和1.2～1.5 g·plant-1),超优质中产型材料1份(≥9.54 g·kg-1和0.874 g·plant-1)；质中超高产型材料1份(8.062 g·kg-1和1.626 g-plant-1),质次超高产型材料1份(7 g·kg-1和1.58 g-plant-1)。
③生长期型种质材料筛选：根据生长期长短,划分为超早熟型(或超短生长期型)、早熟型(或短生长期型)、中熟型(或中生长期型)、晚熟型(或长生长期型)、超晚熟型(或超长生长期型)。其中,多数晚熟型(或长生长期型)材料,来自(或最初来自)武陵山地域,其生长期与其它材料截然分开,可能是该地区资源保持独特优质地域性的原因。
④其它性状种质类型：试验共分出3种株型：分枝型、主干型、丛生型,3种茎色型：紫色、黄色和绿色；不同一级分枝数等类型：根据本试验可以分多分枝型、少一级分枝型等。
(3)主要农艺性状与青蒿素含量和产量的相关性
①青蒿素含量与单株叶产量呈显著正相关,与其它生物量指标包括主茎、枝干重、地上部分、根干重、总生物量等之间相关关系都不显著,与生物量比重各指标不显著。青蒿素含量与株高、茎粗、一级分枝数和一级分枝长等形态指标之间相关关系都不显著。3种茎色青蒿材料间,紫色极显著高于绿色,显著高于黄色,后两者差异不显著。
青蒿素含量与现蕾期、始花期、盛花期有一定程度正相关性但也未达到显著水平。按4种生长期类型统计,则发现生长期过短过长都不利青蒿素含量,晚熟型平均最高,与中熟型的均值间差异未达显著水平,但显著高于早熟型,极显著高于超晚熟型。
②青蒿素单株产量与青蒿素含量、单株叶产量、主茎、分枝、地上部分、根干重、总生物量极显著正相关,与株高极显著正相关,与茎粗、一级分枝数显著正相关,但与各生物量比重指标相关性不显著,与一级分枝长关系不显著。
3种株型中,分枝型极显著高于丛生型,主干型居中,与两者差异都不显著。3种茎色型中,紫色茎杆极显著高于绿色,黄色茎杆居中,与紫色、绿色的差异均不显著。
生长期：晚熟型平均1.102 g·plant-1最高,与中熟型的均值0.881 g·plant-1间差异未达显著水平,但显著高于早熟型的0.636 g·plant-1,极显著高于超晚熟型的0.380g·plant-1;中熟型与早熟型差异不显著,但显著高于超晚熟型；早熟型与超晚熟型间差异未达显著水平。
(4)青蒿素含量、产量与主要农艺性状回归方程的建立与通径分析
青蒿素含量、产量分别与主要农艺性状(生物量、生物量比重、植株形态生长期等指标)建立起线性逐步回归方程和二次多项式逐步回归方程,二次多项式的拟合度更好。回归和通径分析表明,一定程度可依据某些农艺性状判断种质的叶产量、青蒿素单株产量甚至青蒿素含量,但判断青蒿素含量的可靠性并不大。
4氮磷钾肥和密度对青蒿生长和青蒿素产量的影响
L16(45)正交设计田间试验,研究氮磷钾肥和密度对青蒿生长和青蒿素产量的效应,结果表明氮磷钾肥和种植密度的单因素及其组合对青蒿株高、茎粗、生物量、青蒿素含量与产量、青蒿叶养分含量与累积量等指标都影响极大,合理的肥料用量和密度对青蒿种植十分重要。其中,对青蒿个体和群体的生物量作用效果氮肥和密度较磷、钾肥大,对叶片青蒿素含量的影响氮、钾肥比磷肥和密度更为突出。
(1)单因素效果
氮肥：适量氮肥有利于青蒿株高和茎粗的生长,但对一级分枝数作用不大；增加青蒿单株和群体的生物量积累、叶产量,增加青蒿叶部氮磷钾养分的含量和累积量,但高水平的施氮对上述指标进一步增加作用有限,甚至一定程度降低叶钾含量和累积量；适度的氮肥显著提高青蒿素含量和产量,但容易过量,过量氮大幅度降低青蒿素含量,从而降低青蒿素产量。因而对青蒿素含量和产量而言,把握氮肥用量很重要,综合各指标特别是青蒿素含量和青蒿素群体产量,最适宜的施氮水平为尿素650(N300) kg·hm-2。
磷肥：增加青蒿株高和茎粗,对一级分枝数有一定正效应；增加高青蒿生物量积累和叶产量,青蒿叶部氮磷钾养分的含量和累积量；提高叶片青蒿素含量和产量。但高水平施磷对青蒿生长、生物量积累、叶产量、叶部养分含量和积累、青蒿素含量和产量的进一步提升效应并不显著,虽然如此,也没有如氮那样因过量而产生负效应的现象。同时,磷对叶生物量比重也没有明显效果。就单因素肥效应而言,施普钙量应该不少于1250 (P2O5150) kg·hm-2,但同时综合磷肥效应和肥料效益,最适宜的施磷水平为普钙1250-2500(P2O5150～300) kg·hm-2。
钾肥：增加青蒿的株高和茎粗,对分枝数没有效应；有降低叶氮、叶磷含量的效应,但增加叶钾含量和叶氮磷钾累积量；对青蒿总生物量和叶产量、青蒿素含量和产量,有与磷肥相似的提升效应且没有负效应,提高青蒿素含量的作用较磷更强。综合钾肥效应和肥料效益,最适宜的施钾水平为氯化钾350(K2O210) kg-hm-2。
密度：对株高总体上稍有降低作用,而减小茎粗作用强,对一级分枝数没有作用;青蒿个体植株的总生物量和叶产量随种植密度增大而极显著减少,但适当增大密度能提高群体总生物量和叶产量,也有利光合产物形成叶产量：高密度降低叶部氮磷养分含量,同时因减少了单株叶产量,因而对叶部养分的单株累积量的减少作用极显著,但对叶部养分的小区累积量是增加的。过高的密度会显著降低青蒿素含量,降低单株和群体的青蒿素产量。以青蒿素小区产量来看,适宜的种植密度为25000 plant·hm-2。
(2)试验处理组合间效果比较
本试验16个组合处理彼此间的青蒿形态、养分、生物量、青蒿素含量和产量等约20个指标,彼此之间差异大。因此优选很有必要,其中：单株叶产量高低相差2.12倍、小区叶产量2.76倍,青蒿素含量高低相差1.2倍,青蒿素单株产量高低相差2.3倍、青蒿素小区产量3.2倍。
(3)合理肥密的组合方案优选
氮磷钾肥和密度对青蒿的各主要指标的作用效应是不一致的,而种植生产中,当以青蒿素小区产量和青蒿素含量作为种植的最终目标。
据此,本试验组合的优选方案为处理12(N3P4K2密度3,即N300 kg·hm-2、P2O5450 kg·hm-2、K2O 105 kg·hm-2、密度25000 plant·hm-2),可以获得青蒿素最高小区产量,同时青蒿素含量也高。
按单因素效应的优选方案为：施氮水平3(N 300 kg·hm-2),施磷≥水平2(P2O5 150 kg·hm-2),施钾≥水平3(K2O 210 kg·hm-2),种植密度水平3(25000 plant·hm-2)。
因此,单因素最优的组合和处理12在进一步对比试验后,可以形成合理施肥、合理密度的青蒿优质高产的技术方案,并推广到重庆青蒿主产区的生产实践中。
(4)青蒿素含量、产能与植物形态、叶部养分间的相关性
青蒿素含量与叶钾含量极显著正相关,与叶氮含量、叶磷含量不显著；与茎粗极显著正相关；与单株叶产量、单株总生物量的存在不太紧密的正相关性。
青蒿素单株产量与叶氮、叶钾含量显著正相关,与叶磷含量相关性也比较高(p=0.072)。
青蒿素小区产量与叶氮含量显著正相关,与叶磷、叶钾含量相关性不显著。
(5)青蒿素含量产能与植物形态、叶部养分间回归模型
以青蒿形态、叶部养分指标为自变量,建立青蒿叶产量、青蒿素含量、青蒿素产量的线性逐步回归方程,方程的显著性检验、决定系数和Durbin-Watson统计量表明所建模型好而有效。其中,
①单株叶产量=-158.46+152.6·茎粗+5.737·叶氮含量-32.803·叶磷含量-5.559·叶钾含量(R2=0.9576,p=0.0000)。
②当调整相关系数Ra最大时,青蒿素含量=8.4043+0.8443·茎粗-0.06296·级分枝数+0.08246·叶钾含量(R2=0.8471,p=0.0000)。当以回归系数完全显著时,青蒿素含量=5.2187+0.1108·叶钾含量(R2=0.7875,p=0.0000),仅叶钾含量为自变量。
③青蒿素单株产量=1.2111-0.01845·一级分枝数+0.1129·叶氮单株累积量+0.1528·叶钾单株累积量(R2=0.9909,p=0.0000)。
④青蒿素小区产量=24.5481-0.9067·叶氮含量+0.2272·叶氮小区累积量+0.2498·叶钾含量+0.4517·叶钾单株累积量(R2=0.9915,p=0.0000)。
上述方程和通径一致显示,叶养分中,氮磷特别是氮对生物产量作用大,而钾对青蒿素含量作用重要。
Artemisia annua L, a annual herb of the Asteraceae, is a traditional Chinese medicine with functions of clearing heat, expelling hot-dampness and antimalaria. Its leaves and bud contain artemisinin and it's the only commercial source of artemisinin at present. Chinese scholars isolated artemisinin from Artemisia annua L and developed artemisinin-based combination therapies (ACT) independently according to traditional Chinese medicine in the 1970s. The ACT, widely recognized by the world because of high efficiency, quick action, safety against malaria, was accepted into World Pharmacopoeia and had been adopted by over 50 countries as the first-line malaria treatment with recommendation of the World Health Organization (WHO).
Artemisia annua L is a world wide distribution species, but the vast majority of it has no use in industrial extraction due to very low concentration of artemisinin, except a very few with relatively higher from a few areas in Asia. Chongqing is a one of these areas. So, It's very meanful to develop planting industry of Artemisia annua L in such areas, especially in Chongqing. First, it is of great social significance to save millions of malaria patients; second, it has great economic benefits to make advantages of the unique resources into drugs in short supply. Meanwhile, it set up traditional Chinese medicine a good reputation and guide the other traditional Chinese medicine to the world.
However, it is crucial to plant Artemisia annua L for artemisinin production. Now we face very urgent and key scientific question:how we can enhance the concentration and yield of artemisinin in field? The aim here is to enhance artemisinin by two conventional routes of germplasm and cultivation. This paper consists of 4 main parts of research as below to provide the scientific basis for the resource protection of Artemisia annua L and high yield production of artemisinin.
1 Artemisinin determination
(1) Establishment and evaluation of determination method
Determination methods were established for artemisinin in Artemisia annua L by UV-Spectrophotometry and HPLC respectively. Methodology study proved them simple, stable, accurate and reproducible. Comparison (t-test) of 9 samples determination with 2 replication showed no significant difference between two methods (p=0.4527).
(2) Extraction of sample
The orthogonal test (L9(34)) was adopted to examine the effects of extraction agant, volume of agent, temperature and time on artemisinin extraction from sample. The results showed that temperature was the most crucial factors and 40℃was the best; different extractants had significant difference and petroleum ether(30-60℃) was the best; the volume of agent and time had high significant influence on extraction and the best were 50 mL(per gram sample) of agent usage and 2 hours of time respectively.
A further comparison test showed that:Ultrasonic treatment can shorten extraction time or reduce extraction times, and can reduce extractant consumption; increase of extractant usage can well offset decrease of extraction time; increase of times has more effective than increase of time. At last,5 combinations of factors above were selected as optimal extraction methods.
(3) Postharvest drying of sample
Sun drying or 40℃oven drying benefited artemisinin concentration, and sample left in the shade for lday before sun drying or 40℃oven drying had no significant difference in artemisinin concentration; the samples at air drying had significant lower artemisinin concentration; when samples dried in oven at more than 40℃, artemisinin concentration reduced high significantly with increase of temperature.
(4) Storage of sample
Storage time, temperature, sample moisture content and package had high significant effects on artemisinin content in sample during storage. Artemisinin content decreased with the storage time, gently in the former 2 months and but rapidly later; with more moisture content in samples, artemisinin content decreased more; artemisinin content at room temperature decreased more than that at 4℃; the influence of the package depends on moisture and temperature:at low temperature, artemisinin content sorted down in order of paper packing+plastic packing+desiccant> plastic packing> paper packing; but in high moisture and at room temperature, all plastic packing accelerated degradation of artemisinin.
The actual function of package is waterproof. Therefore, the key things during storage are to keep sample in low moisture and at low temperature. The samples with low moisture content (5%-7%) which dried at 40℃oven before storage could still have about 90% artemisinin left after storage of one year at 4℃(even 95.5% artemisinin left with package of paper packing+plastic packing+desiccant). On the contrary, the samples with high moisture content (15%-16%) dried in air before storage were useless for less 30% artemisinin left after one year storage at normal temperature.
2 Resources and habitats of Artemisia annua L in Chongqing
148 sampling sites (79 in 2005 and 69 in 2009) were investigated, and leaves of Artemisia annua L and soils were sampled.
(1) Quality of Artemisia annua Lin Chongqing
Artemisinin concentration in leaves of Artemisia annua L in Chongqing averaged 5.92g·kg-1 with change of 1.09～13.03g·kg-1.
Quality of the Artemisia annua L characterized strong regional distribution:the artemisinin concentration in Artemisia annua L in southeast region(Youyang) was the highest, significant higher than that in other 3 regions (about 1.5-2.5 times), especially that of wild Artemisia annua Lin 2005.
Quality of the cultivated were higher by 34.5% in 2005,24.4% in 2009 and 29.5% (average) in total 2 years than that of the wild respectively. Cultivation improved not only the quality but also uniformity of the Artemisia annua.
Quality of the Artemisia annua L had a modest increase(7.88%) from 2005 to 2009 in Chongqing. Among them, urban region(Beibei), east region (Wanzhou) and west region(Yongchuan) had greater increases or tended to increase while southeast region(Youyang) decreased 9.57%(11.1% for the wild and 8.10% for the cultivated).
(2) Habitat factors on quality of Artemisia annua L
Hydrological condition, light intensity and soil texture affected quality of the Artemisia annua L high significantly. The best hydrological condition averaged 2.26 times artemisinin concentration to the drought condition. Shade decreased the artemisinin concentration in leaves, and the artemisinin concentration varied 3.3 times among the four light classifications. Among the four classifications of soil texture, medium loam was the most suitable for Artemisia annua L, then light loam and heavy loam, sandy loam was adverse to the artemisinin concentration.
Three kinds of soil (puddy soil, purple soil and yellow soil) had no significant differences of artemisinin concentration in cultivated Artemisia annua L. In wild Artemisia annua L, puddy soil and purple soil were significantly superior to yellow soil.
(3) Habitat soil nutrients
Organic matter, available nitrogen, available phosphorus and available potassium were measured. All nutrients above positively correlated with artemisinin concentration.
(4) Regression model between artemisinin concentration and soil nutrients
Artemisinin content, as the dependent variable (Y), fit well regression models like linear stepwise regression, quadratic polynomial stepwise regression and higher degree linear in stepwise regression (a new statistical method by this paper) with soil nutrients (including organic matter, available nitrogen, available phosphorus and available potassium, as the independent variables). All of regression coefficients and path analysis indicated that not only the nutrients but also the nutrient ratios in soil were important to artemisinin concentration. Therefore, when growing Artemisia annua L we had to take account of both nutrient quantity and nutrient balance in soil.
(5) Soil nutrient norm and diagnosis for high quality Artemisia annua L in Chongqing
Sifted out the sampling sites on extreme condition of hydrology and shade and the sampling sites with medium artemisinin concentration, the rest sampling sites were divided into high artemisinin concentration group and low artemisinin concentration group. T-test showed that nutrients (avail N, avail P, avail K) in soil and nutrient ratios (N/P, N/K, P/K) all were high significant differences between the two groups. With reference DRIS method of plant nutrition, the average nutrients (avail N, avail P, avail K) and their ratios (N/P, N/K, P/K) in soils of the high group and confidence limits were presented as norm and diagnosis for high quality production of Artemisia annua L in Chongqing.
3 Comparison and screening of Artemisia annua L germplasm
(1) Character comparisons between germplasm materials
50 germplasm materials from Chongqing and surrounding provinces were grown in field in 2006 under the same water and fertilizer management, most of them had great difference with each other in21 indices of artemisinin concentration, artemisinin yield per plant, biomass, biomass ratio, morphology and growth period. The enormous differences also illustrated the richness of Artemisia annua L resource and proved very essential for germplasm screening.
(2) Germplasm material screening
①Quality-types:6 materials with more than 9.5 g-kg-1 of artemisinin concentration were screened out as super-high-quality-type and7 materials with 8.5～9.5 g-kg-1 of artemisinin concentration as high-quality-type.
②Quality-and-productivity-types:3 materials were screened out as high-quality-and-super-productivity-type (with 8.5～9.5 g-kg-1 and=1.5 g-plant-1 of artemisinin),5 materials as super-quality-and-high-productivity-type(=9.5 g-kg-1 and 1.2～1.5 g-plant-1 of artemisinin),1 material as super-quality-and-medium-productivity-type (=9.5 g-kg-1 and 0.874 g-plant-1 of artemisinin),1 material as medium-quality-and-super-productivity-type (8.062 g-kg-1 and 1.626 g-plant-1 of artemisinin),1 material as inferior-quality-and -super-productivity-type(7 g-kg-1 and 1.58 g·plant-1 of artemisinin).
③Maturity types:The materials were divided into 4 maturity types by growth period:early maturity type, medium maturity type, late maturity type and super late maturity type. Most of the late maturity type materials come from Mountain Wuling area. Their flowering stage almost separated from the other maturity types, which may be the reason of unique character of high quality.
④Other types:Materials in experiment were divided into 3 plant form types of limb type (16%), straightstem type (66%) and tuft type (18%),3 stem colour types of purple, yellow and green, and other types.
(3) Correlation of quality and productivity with main agronomic characters
①Artemisinin concentration had a significantly positive correlation with leaf yield perplant, but no significant correlation with other indices of biomass and biomass ratio, nor with morphological indices (plant height, stem diameter, primary branch number and lenth of the longest primary branch). Among 3 germplasm types of stem colour, purple stem had highest average artemisinin concentration, significantly higher than green stem, and very significantly higher than yellow stem; while there was no significant difference between green stem and yellow stem.
Artemisinin content had a certain positive but no significant correlation with lenth of growth period. Whereas according to 4 maturity types, there were differences. The late maturity type averaged highest, no significant difference with medium maturity type, significantly higher than early maturity type and very significantly higher than super late maturity type.
②Artemisinin yield perplant had a high significant positive correlation with artemisinin concentration, biomass perplant of leaf/stem/branch/aerial part/root/total biomass, high significant positive with plant height, significant with stem diameter and primary branch number, but no significant with any biomass ratio indexes, nor with lenth of the longest primary branch.
Among 3 kinds of plant form types, limb type had the most average artemisinin yield perplant, very significantly more than that of tuft type; straightstem type had the second, but no difference from limb type, nor from tuft type. Among 3 types of stem colour, the purple was high significantly more than the green; the yellow averaged the second, no difference from the purple stem and the green.
Among 4 types of growth period:late maturity type averaged the most of 1.102 g·plant-1, no significant difference with 0.881 g·plant-1 of medium maturity type, significantly more than 0.636 g·plant-1 of early maturity type and very significantly more than 0.380 g·planf'of super late maturity type.
(4) Regression models between main agronomic characters and artemisinin concentration, yield perplant
Regression equations, linear stepwise regression and quadratic polynomial stepwise regression, were established between artemisinin concentration, leaf yield perplant and artemisinin yield perplant respectively with the main agronomic characters (indices of biomass, biomass ratio, morphology and growth period). The models of quadratic polynomial stepwise regression fit better than linear stepwise regression. Regression and path analysis showed that some agronomic characters can to some extent be used as indices for predetermination leaf yield perplant, artemisinin yield perplant, even artemisinin concentration (but low reliability), or to say, for screening germplasm of high-artemisinin-productivity.
4 Effects of application of fertilizer N, P and K and planting density on the growth of Artemisia annua L and the yield of artemisinin
A field experiment with an orthogonal design (L16(45)) was conducted to study the effects of different doses of fertilizer N, P and K and different planting densities on the growth of Artemisia annua L and the yield of artemisinin which provides a scientific basis for the Artemisia annua L cultivation and artemisinin production. The results showed that:
(1) Effects of single factor
Fertilizer nitrogen:nitrogen in moderate supply was advantageous to growth of plant height and stem diameter, but no significant influence on primary branch number; Nitrogen in moderate supply enhanced significantly biomass production (leaf yield and total biomass), leaf N(concentration and accumulation), leaf P(concentration and accumulation), leaf K(concentration and accumulation), artemisinin concentration in leaf and artemisinin yield under both perplant and perplot; Ample N benefited the leaf yield, excess nitrogen had no significant influences on biomass, leaf N and leaf P, but a significant negative effects on leaf K, artemisinin concentration and artemisinin yield. Therefore, contol amount of nitrogen application was essential for growth of Artemisia annua L and artemisinin production. The optimal nitrogen application was urea 650(N300) kg·hm-2.
Fertilizer phosphorus:Phosphorus application increased plant height, stem diameter, primary branch number, leaf yield, total biomass, leaf N(concentration and accumulation), leaf P(concentration and accumulation), leaf K(concentration and accumulation), artemisinin concentration in leaf and artemisinin yield; High level supply of phosphorus showed no significant further positive nor negative effects. Therefore, maximization of artemisinin concentration in leaf and artemisinin yield required phosphorus amount of over 1250 (P2O5150) kg·hm-2. In consideration of efficiency, the suitable amount of phosphorus application was calcium superphosphate1250～2500 (P2O5150～300) kg-hm-2.
Fertilizer potassium:Potassium application had significant effects on increases of plant height and stem diameter, but no significant influence on primary branch number; Inreases in potassium supply dereased leaf N concentration and leaf P concentration, however, increased leaf K(concentration and accumulation), leaf N accumulation and leaf P accumulation. As phosphorus did, potassium application increased leaf yield, total biomass, artemisinin concentration in leaf and artemisinin yield, and over amount potassium showed no significant infulences on biomass and artemisinin. Potassium had a more effective increase on artemisinin concentration than phosphorus did. Therefore, in consideration of comprehensive efficiencies, the suitable amount of potassium application was potassium chloride 350 (K2O 210) kg-hm-2.
Planting density:With increases of planting density, plant height decreased slightly and primary branch number showed no change, and stem diameter and biomass perplant (leaf and total) decreased successively. Moderate increases of planting density increased biomass per plot (group biomass of leaf and total). High density decreased leaf N concentration and leaf P concentration slightly; over crowded density significantly decreased artemisinin concentration and artemisinin yield (both perplant and perplot). By the artemisinin yield per plot, the optimal planting density was 25000 plant9hm-2
(2) Multiple comparisons of treatments
16 treatments in the experiment differentiated greatly from each other in 20 indices of morphology, biomass, leaf nutrition and artemisinin concentration and yield. Among them, leaf yield perplant/perplot varied 2.12/2.76 times, artemisinin concentration variedl.2 times, artemisinin yield perplant/perplot varied 2.3/3.2 times. So it's necessary to evaluate and select the optimal combination of treatment.
(3) Optimization of fertilizer N, P and K and planting density
The ultimate indexes for optimization of fertilizer N, P and K and planting density are artemisinin yield in population (per plot) and artemisinin concentration.
According to multiple comparisons of treatments, the optimization was treatment12(N3P4K2density3:it means N300 kg-hm-2, P2O5450 kg-hm-2, K2O 105 kg-hm-2 and density 25000 plant·hm-2), which can get yield of 36.42 kg·hm-2 with higher artemisinin concentration.
According to effects of single factor, the optimization (the combination of optimal single-factors) should be N300 (urea 650) kg-hm-2, P2O5150～300(calcium superphosphate1250～2500) kg-hm-2, K2O 210(potassium chloride 350) kg·hm-2 and 25000 plant·hm-2 of planting density. The optimization was not any of 16 treatments in this experiment, its combination effects and artemisinin productivity need a further test.
Therefore, a further comparative test need to evalue above. After this, the optimizations can be put into practice in Chongqing.
(4) Correlation of artemisinin concentration and yield with morphology and leaf nutritions (N, P and K)
Artemisinin concentration had a high significantly positive correlation with concentration of leaf K, but no significant correlation with that of leaf N and leaf P; a high significantly positive correlation with stem diameter; a positive correlation with leaf yield perplant and total biomass perplant in relatively high extent.
Artemisinin yield perplant had a significantly positive correlation with concentration of leafN and leaf K, and a positive correlation with leaf P concentration in relatively high extent (p=0.072).
Artemisinin yield per plot had a significantly positive correlation with concentration of leaf N, but no significant correlation with that of leaf P and leaf K.
(5) Linear stepwise regression of leaf yield, artemisinin concentration and yield with morphology and leaf nutritions (N, P and K)
Indexes of morphology and leaf nutritions as the independent variables:
①Leaf yield perplant=-158.46+152.6·stem diameter+5.737·leaf N concentration-32.80·leaf P concentration-5.559'leaf K concentration (R-=0.9576, p=0.0000).
②When adjusting correlation coefficient reached maximum:artemisinin concentration=8.404325+0.844350·stem diameter-0.0629605·primary branch number +0.0824598·leaf K concentration (R2=0.8471, p=0.0000). When all regression coefficients satisfy the significant level (p=0.05):Artemisinin concentration=5.2187+ 0.1108·leaf K concentration (R2=0.7875, p=0.0000).
③Artemisinin yield perplant=1.2111-0.01845·primary branch number+0.1129·leaf N accumulation perplant+0.1528·leaf K accumulation perplant (R2=0.9909, p=0.0000).
④Artemisinin yield per plot=24.5481-0.9067·leaf N concentration+0.2272·leaf N accumulation perplot+0.2498·leaf K concentration+0.4517·leaf K accumulation perplant (R2=0.9915, p=0.0000).
Significance test, determination coefficient and Durbin-Watson statistic of the regressions showed that equations above were good and valid. The regressions and their path analyses proved that leaf N and leaf P (especially leaf N) important to leaf yield and leaf K important to artemisinin concentration.
青蒿虽是世界性的广布物种,但仅极少数地区青蒿素含量相对较高,能达到工业提取水平之上。而重庆则是这极少数地区之一。在这极少数地区发展青蒿种植业,可以拯救数以亿计疟疾患者,具有极重大社会意义,而且,有利于将独特资源优势转化为经济优势,也具有极显著经济效益。同时,青蒿素也为传统中药树立形象,对其它中药走向世界具有引领作用。
青蒿种植和青蒿素生产具有如此重要意义,那么,选育高含量品种,以及通过栽培技术提高青蒿素含量和产能,成为我们面临的关键而十分紧迫的课题。特别是青蒿素含量至关重要。基于此,本文以提高青蒿素为研究核心,围绕种质筛选和栽培两个方向,展开4个部分的研究：
1青蒿素含量的测定
(1)测定方法的建立与评价
分别建立紫外分光光度法(UVSPM)和高效液相色谱法(HPLC)测定青蒿素,方法学研究表明两方法操作简便、稳定性高、精度准、重现性好。分别对9个样品两次重复进行测定,结果经t检验,表明两种方法测定青蒿素含量的没有差异(p=0.4527)。
(2)样品的提取
采用(L9(34))正交试验方案,研究提取溶剂、溶剂用量、提取温度和提取时间4因素对提取效果的影响,结果表明：提取温度是最为关键的因素,40℃最佳,低于或高于40℃提取效果都不好；提取溶剂对提取影响显著,宜选石油醚(30-60℃)；提取剂用量(料液比)对提取效果影响极显著,宜选50 mL；提取时长对提取结果影响极显著,宜选2小时。
进一步对比试验表明：超声波可以缩短提取时间或降低提取次数,同时可减少提取溶剂用量；增加取剂用量和缩短提取时间之间,可以很好互相弥补,增加提取次数比延长提取时间更有效。5种组合方案为优选提取方法,它们提取效果好,彼此无差异。
(3)样品采后干燥方法
晒干、40℃烘干效果最佳,阴1天后再晒干或40℃烘干,对结果也没有显著影响；自然风干则含量显著降低；烘干超过40℃后,青蒿素含量则随温度升高而极显著降低。
(4)样品储存
储存时长、温度、样品水分含量和包装4因素对青蒿储存过程中青蒿素含量变化影响都极显著。青蒿素含量随储存时间而降低,但前2个月,趋势总体上相对平稳,之后降幅增大、降速加快；样品水分含量越高青蒿素衰降越快且幅度越大；4℃低温青蒿素衰降比常温平稳；包装的影响则取决于样品的水分含量和温度,低温时：青蒿素含量高低顺序为：纸袋+塑料袋+干燥剂>塑料袋>纸袋,高水分含量、室温时,凡有塑料袋都加速青蒿素衰降。
包装的实际作用是防潮,因此,除时间外,样品储存的最关键因素是样品水分含量和温度,即样品始终要处在低水分含量、低温度条件下。干燥度高(储存前40℃烘干至恒重的样品,水分含量5%-7%),4℃低温条件,储存1年后青蒿素还保有90%左右,采用纸袋+塑料袋+干燥剂的包装,最好效果青蒿素含量可以1年后仍然有95.5%。相反,而湿润环境下的样品风干样(水分含量15%-16%)、室温储存,无论什么包装,长时间储存都会让青蒿变得没有价值,1年后,青蒿素含量最低仅剩不到30%左右。
2重庆青蒿资源及生境调查
分别于2005、2009年共调查重庆148个样品点青蒿及其生境,结果如下：
(1)青蒿品质
全市平均青蒿素含量为5.92g·kg-1,幅度1.09-13.03g·kg-1。
青蒿品质表现很强的地域性的分布特点：渝东南(酉阳)片区含量最高,极显著高于其他3片区,是其它3片区的1.5-2.5倍左右,尤其2005年野生资源。
栽培青蒿品质较野生青蒿有极显著提高,2005、2009年和两年总计全市栽培较野生青蒿素含量分别提高34.5%、24.4%和29.5%,同时栽培也提高了青蒿品质的整齐度。
从时间演变来看,2009年品质较2005年总体上有小幅提高(7.88%)。其中,主城(北碚)、渝东(万州)和渝西(永川)有较大幅度提高或提高趋势；但优质资源地的渝东南(酉阳)则呈相反的变化,野生和栽培青蒿品质都呈下降趋势(野生、栽培和总平分别下降11.1%、8.10%、9.57%)。
(2)生境因子
水文、光照和土壤质地极显著地影响青蒿素含量,土壤类型的影响则很小。水文条件好,青蒿素含量愈高,且变异系数越小,4个水文等级青蒿素含量高低相差2.26倍。光照充足有利于青蒿素含量提高,遮荫则大幅降低青蒿素含量,4个光照等级青蒿素含量高低相差3.3倍。4个质地等级中,最适宜的质地为“偏重”,然后为“偏轻”和“重”,质地“沙”不利于青蒿中的青蒿素。
调查的中的紫色土、水稻土、黄壤3种土壤类型对栽培青蒿的品质没有影响,野生青蒿则水稻土、紫色土显著高于黄壤。
(3)生境土壤养分及与青蒿素含量相关性
土壤有机质、碱解氮、有效磷和速效钾被测定。青蒿素含量与上述土壤养分均极显著正相关。
(4)青蒿素与生境的土壤养分回归数量模型和通径分析
以青蒿素含量为因变量(Y),有机质(X1)、碱解氮(X2)、有效磷(X3)和速效钾(X4)为自变量,分别能较好建立线性逐步回归、二次多项式逐步回归和引入高次及养分比的线性逐步回归方程式,回归系数和通径分析表明,影响青蒿素含量不仅有养分绝对数量和养分间交互作用,养分比例也同样发挥着重要作用。因此,青蒿种植需同时兼顾土壤中的养分数量和养分平衡。
(5)重庆优质青蒿的土壤养分标准与诊断
去掉水文光照条件极端、青蒿素含量居中的样点,剩下分为青蒿素高含量和低含量两个样本群组, t-检验比较土壤养分和养分比例,都存在显著性差异。采用植物营养中养分综合诊断法,以高含量组土壤平均有效氮磷钾及其比例平均值,结合其一定范围的置信限,建立重庆优质青蒿的土壤养分标准,按这一标准进行养分诊断和推荐施肥。
3青蒿种质材料评比与筛选
(1)种质材料间性状差异
50份来源于重庆及周边省份青蒿种质材料,田间试验,在同一肥水、环境和管理条件下,多数不同种质材料间不仅在青蒿素含量、青蒿素单株产量存在极大差异,还在生物量、生物量比重、植株形态、生长期共计21个指标存在极显著差异。巨大的差异,不仅表明青蒿材料间差异大,也更表明青蒿种质资源的丰富,还表明种质材料筛选很必要。
(2)种质材料筛选
①优质种质材料筛选：按青蒿素含量高低,筛选出高含量材料13份,其中,超过9.5 g·kg-1的超优质材料6份,8.5-9.5 g·kg-1的优质材料7份。
②高品质与高产能的复合筛选：按青蒿素含量和单株青蒿素产量,筛选出优质超高产型材料3份(青蒿素含量产量分别8.5-9.5g·kg-1和≥1.5 g·plant-1),超优质高产型材料5份(≥9.5 g·kg-1和1.2～1.5 g·plant-1),超优质中产型材料1份(≥9.54 g·kg-1和0.874 g·plant-1)；质中超高产型材料1份(8.062 g·kg-1和1.626 g-plant-1),质次超高产型材料1份(7 g·kg-1和1.58 g-plant-1)。
③生长期型种质材料筛选：根据生长期长短,划分为超早熟型(或超短生长期型)、早熟型(或短生长期型)、中熟型(或中生长期型)、晚熟型(或长生长期型)、超晚熟型(或超长生长期型)。其中,多数晚熟型(或长生长期型)材料,来自(或最初来自)武陵山地域,其生长期与其它材料截然分开,可能是该地区资源保持独特优质地域性的原因。
④其它性状种质类型：试验共分出3种株型：分枝型、主干型、丛生型,3种茎色型：紫色、黄色和绿色；不同一级分枝数等类型：根据本试验可以分多分枝型、少一级分枝型等。
(3)主要农艺性状与青蒿素含量和产量的相关性
①青蒿素含量与单株叶产量呈显著正相关,与其它生物量指标包括主茎、枝干重、地上部分、根干重、总生物量等之间相关关系都不显著,与生物量比重各指标不显著。青蒿素含量与株高、茎粗、一级分枝数和一级分枝长等形态指标之间相关关系都不显著。3种茎色青蒿材料间,紫色极显著高于绿色,显著高于黄色,后两者差异不显著。
青蒿素含量与现蕾期、始花期、盛花期有一定程度正相关性但也未达到显著水平。按4种生长期类型统计,则发现生长期过短过长都不利青蒿素含量,晚熟型平均最高,与中熟型的均值间差异未达显著水平,但显著高于早熟型,极显著高于超晚熟型。
②青蒿素单株产量与青蒿素含量、单株叶产量、主茎、分枝、地上部分、根干重、总生物量极显著正相关,与株高极显著正相关,与茎粗、一级分枝数显著正相关,但与各生物量比重指标相关性不显著,与一级分枝长关系不显著。
3种株型中,分枝型极显著高于丛生型,主干型居中,与两者差异都不显著。3种茎色型中,紫色茎杆极显著高于绿色,黄色茎杆居中,与紫色、绿色的差异均不显著。
生长期：晚熟型平均1.102 g·plant-1最高,与中熟型的均值0.881 g·plant-1间差异未达显著水平,但显著高于早熟型的0.636 g·plant-1,极显著高于超晚熟型的0.380g·plant-1;中熟型与早熟型差异不显著,但显著高于超晚熟型；早熟型与超晚熟型间差异未达显著水平。
(4)青蒿素含量、产量与主要农艺性状回归方程的建立与通径分析
青蒿素含量、产量分别与主要农艺性状(生物量、生物量比重、植株形态生长期等指标)建立起线性逐步回归方程和二次多项式逐步回归方程,二次多项式的拟合度更好。回归和通径分析表明,一定程度可依据某些农艺性状判断种质的叶产量、青蒿素单株产量甚至青蒿素含量,但判断青蒿素含量的可靠性并不大。
4氮磷钾肥和密度对青蒿生长和青蒿素产量的影响
L16(45)正交设计田间试验,研究氮磷钾肥和密度对青蒿生长和青蒿素产量的效应,结果表明氮磷钾肥和种植密度的单因素及其组合对青蒿株高、茎粗、生物量、青蒿素含量与产量、青蒿叶养分含量与累积量等指标都影响极大,合理的肥料用量和密度对青蒿种植十分重要。其中,对青蒿个体和群体的生物量作用效果氮肥和密度较磷、钾肥大,对叶片青蒿素含量的影响氮、钾肥比磷肥和密度更为突出。
(1)单因素效果
氮肥：适量氮肥有利于青蒿株高和茎粗的生长,但对一级分枝数作用不大；增加青蒿单株和群体的生物量积累、叶产量,增加青蒿叶部氮磷钾养分的含量和累积量,但高水平的施氮对上述指标进一步增加作用有限,甚至一定程度降低叶钾含量和累积量；适度的氮肥显著提高青蒿素含量和产量,但容易过量,过量氮大幅度降低青蒿素含量,从而降低青蒿素产量。因而对青蒿素含量和产量而言,把握氮肥用量很重要,综合各指标特别是青蒿素含量和青蒿素群体产量,最适宜的施氮水平为尿素650(N300) kg·hm-2。
磷肥：增加青蒿株高和茎粗,对一级分枝数有一定正效应；增加高青蒿生物量积累和叶产量,青蒿叶部氮磷钾养分的含量和累积量；提高叶片青蒿素含量和产量。但高水平施磷对青蒿生长、生物量积累、叶产量、叶部养分含量和积累、青蒿素含量和产量的进一步提升效应并不显著,虽然如此,也没有如氮那样因过量而产生负效应的现象。同时,磷对叶生物量比重也没有明显效果。就单因素肥效应而言,施普钙量应该不少于1250 (P2O5150) kg·hm-2,但同时综合磷肥效应和肥料效益,最适宜的施磷水平为普钙1250-2500(P2O5150～300) kg·hm-2。
钾肥：增加青蒿的株高和茎粗,对分枝数没有效应；有降低叶氮、叶磷含量的效应,但增加叶钾含量和叶氮磷钾累积量；对青蒿总生物量和叶产量、青蒿素含量和产量,有与磷肥相似的提升效应且没有负效应,提高青蒿素含量的作用较磷更强。综合钾肥效应和肥料效益,最适宜的施钾水平为氯化钾350(K2O210) kg-hm-2。
密度：对株高总体上稍有降低作用,而减小茎粗作用强,对一级分枝数没有作用;青蒿个体植株的总生物量和叶产量随种植密度增大而极显著减少,但适当增大密度能提高群体总生物量和叶产量,也有利光合产物形成叶产量：高密度降低叶部氮磷养分含量,同时因减少了单株叶产量,因而对叶部养分的单株累积量的减少作用极显著,但对叶部养分的小区累积量是增加的。过高的密度会显著降低青蒿素含量,降低单株和群体的青蒿素产量。以青蒿素小区产量来看,适宜的种植密度为25000 plant·hm-2。
(2)试验处理组合间效果比较
本试验16个组合处理彼此间的青蒿形态、养分、生物量、青蒿素含量和产量等约20个指标,彼此之间差异大。因此优选很有必要,其中：单株叶产量高低相差2.12倍、小区叶产量2.76倍,青蒿素含量高低相差1.2倍,青蒿素单株产量高低相差2.3倍、青蒿素小区产量3.2倍。
(3)合理肥密的组合方案优选
氮磷钾肥和密度对青蒿的各主要指标的作用效应是不一致的,而种植生产中,当以青蒿素小区产量和青蒿素含量作为种植的最终目标。
据此,本试验组合的优选方案为处理12(N3P4K2密度3,即N300 kg·hm-2、P2O5450 kg·hm-2、K2O 105 kg·hm-2、密度25000 plant·hm-2),可以获得青蒿素最高小区产量,同时青蒿素含量也高。
按单因素效应的优选方案为：施氮水平3(N 300 kg·hm-2),施磷≥水平2(P2O5 150 kg·hm-2),施钾≥水平3(K2O 210 kg·hm-2),种植密度水平3(25000 plant·hm-2)。
因此,单因素最优的组合和处理12在进一步对比试验后,可以形成合理施肥、合理密度的青蒿优质高产的技术方案,并推广到重庆青蒿主产区的生产实践中。
(4)青蒿素含量、产能与植物形态、叶部养分间的相关性
青蒿素含量与叶钾含量极显著正相关,与叶氮含量、叶磷含量不显著；与茎粗极显著正相关；与单株叶产量、单株总生物量的存在不太紧密的正相关性。
青蒿素单株产量与叶氮、叶钾含量显著正相关,与叶磷含量相关性也比较高(p=0.072)。
青蒿素小区产量与叶氮含量显著正相关,与叶磷、叶钾含量相关性不显著。
(5)青蒿素含量产能与植物形态、叶部养分间回归模型
以青蒿形态、叶部养分指标为自变量,建立青蒿叶产量、青蒿素含量、青蒿素产量的线性逐步回归方程,方程的显著性检验、决定系数和Durbin-Watson统计量表明所建模型好而有效。其中,
①单株叶产量=-158.46+152.6·茎粗+5.737·叶氮含量-32.803·叶磷含量-5.559·叶钾含量(R2=0.9576,p=0.0000)。
②当调整相关系数Ra最大时,青蒿素含量=8.4043+0.8443·茎粗-0.06296·级分枝数+0.08246·叶钾含量(R2=0.8471,p=0.0000)。当以回归系数完全显著时,青蒿素含量=5.2187+0.1108·叶钾含量(R2=0.7875,p=0.0000),仅叶钾含量为自变量。
③青蒿素单株产量=1.2111-0.01845·一级分枝数+0.1129·叶氮单株累积量+0.1528·叶钾单株累积量(R2=0.9909,p=0.0000)。
④青蒿素小区产量=24.5481-0.9067·叶氮含量+0.2272·叶氮小区累积量+0.2498·叶钾含量+0.4517·叶钾单株累积量(R2=0.9915,p=0.0000)。
上述方程和通径一致显示,叶养分中,氮磷特别是氮对生物产量作用大,而钾对青蒿素含量作用重要。
Artemisia annua L, a annual herb of the Asteraceae, is a traditional Chinese medicine with functions of clearing heat, expelling hot-dampness and antimalaria. Its leaves and bud contain artemisinin and it's the only commercial source of artemisinin at present. Chinese scholars isolated artemisinin from Artemisia annua L and developed artemisinin-based combination therapies (ACT) independently according to traditional Chinese medicine in the 1970s. The ACT, widely recognized by the world because of high efficiency, quick action, safety against malaria, was accepted into World Pharmacopoeia and had been adopted by over 50 countries as the first-line malaria treatment with recommendation of the World Health Organization (WHO).
Artemisia annua L is a world wide distribution species, but the vast majority of it has no use in industrial extraction due to very low concentration of artemisinin, except a very few with relatively higher from a few areas in Asia. Chongqing is a one of these areas. So, It's very meanful to develop planting industry of Artemisia annua L in such areas, especially in Chongqing. First, it is of great social significance to save millions of malaria patients; second, it has great economic benefits to make advantages of the unique resources into drugs in short supply. Meanwhile, it set up traditional Chinese medicine a good reputation and guide the other traditional Chinese medicine to the world.
However, it is crucial to plant Artemisia annua L for artemisinin production. Now we face very urgent and key scientific question:how we can enhance the concentration and yield of artemisinin in field? The aim here is to enhance artemisinin by two conventional routes of germplasm and cultivation. This paper consists of 4 main parts of research as below to provide the scientific basis for the resource protection of Artemisia annua L and high yield production of artemisinin.
1 Artemisinin determination
(1) Establishment and evaluation of determination method
Determination methods were established for artemisinin in Artemisia annua L by UV-Spectrophotometry and HPLC respectively. Methodology study proved them simple, stable, accurate and reproducible. Comparison (t-test) of 9 samples determination with 2 replication showed no significant difference between two methods (p=0.4527).
(2) Extraction of sample
The orthogonal test (L9(34)) was adopted to examine the effects of extraction agant, volume of agent, temperature and time on artemisinin extraction from sample. The results showed that temperature was the most crucial factors and 40℃was the best; different extractants had significant difference and petroleum ether(30-60℃) was the best; the volume of agent and time had high significant influence on extraction and the best were 50 mL(per gram sample) of agent usage and 2 hours of time respectively.
A further comparison test showed that:Ultrasonic treatment can shorten extraction time or reduce extraction times, and can reduce extractant consumption; increase of extractant usage can well offset decrease of extraction time; increase of times has more effective than increase of time. At last,5 combinations of factors above were selected as optimal extraction methods.
(3) Postharvest drying of sample
Sun drying or 40℃oven drying benefited artemisinin concentration, and sample left in the shade for lday before sun drying or 40℃oven drying had no significant difference in artemisinin concentration; the samples at air drying had significant lower artemisinin concentration; when samples dried in oven at more than 40℃, artemisinin concentration reduced high significantly with increase of temperature.
(4) Storage of sample
Storage time, temperature, sample moisture content and package had high significant effects on artemisinin content in sample during storage. Artemisinin content decreased with the storage time, gently in the former 2 months and but rapidly later; with more moisture content in samples, artemisinin content decreased more; artemisinin content at room temperature decreased more than that at 4℃; the influence of the package depends on moisture and temperature:at low temperature, artemisinin content sorted down in order of paper packing+plastic packing+desiccant> plastic packing> paper packing; but in high moisture and at room temperature, all plastic packing accelerated degradation of artemisinin.
The actual function of package is waterproof. Therefore, the key things during storage are to keep sample in low moisture and at low temperature. The samples with low moisture content (5%-7%) which dried at 40℃oven before storage could still have about 90% artemisinin left after storage of one year at 4℃(even 95.5% artemisinin left with package of paper packing+plastic packing+desiccant). On the contrary, the samples with high moisture content (15%-16%) dried in air before storage were useless for less 30% artemisinin left after one year storage at normal temperature.
2 Resources and habitats of Artemisia annua L in Chongqing
148 sampling sites (79 in 2005 and 69 in 2009) were investigated, and leaves of Artemisia annua L and soils were sampled.
(1) Quality of Artemisia annua Lin Chongqing
Artemisinin concentration in leaves of Artemisia annua L in Chongqing averaged 5.92g·kg-1 with change of 1.09～13.03g·kg-1.
Quality of the Artemisia annua L characterized strong regional distribution:the artemisinin concentration in Artemisia annua L in southeast region(Youyang) was the highest, significant higher than that in other 3 regions (about 1.5-2.5 times), especially that of wild Artemisia annua Lin 2005.
Quality of the cultivated were higher by 34.5% in 2005,24.4% in 2009 and 29.5% (average) in total 2 years than that of the wild respectively. Cultivation improved not only the quality but also uniformity of the Artemisia annua.
Quality of the Artemisia annua L had a modest increase(7.88%) from 2005 to 2009 in Chongqing. Among them, urban region(Beibei), east region (Wanzhou) and west region(Yongchuan) had greater increases or tended to increase while southeast region(Youyang) decreased 9.57%(11.1% for the wild and 8.10% for the cultivated).
(2) Habitat factors on quality of Artemisia annua L
Hydrological condition, light intensity and soil texture affected quality of the Artemisia annua L high significantly. The best hydrological condition averaged 2.26 times artemisinin concentration to the drought condition. Shade decreased the artemisinin concentration in leaves, and the artemisinin concentration varied 3.3 times among the four light classifications. Among the four classifications of soil texture, medium loam was the most suitable for Artemisia annua L, then light loam and heavy loam, sandy loam was adverse to the artemisinin concentration.
Three kinds of soil (puddy soil, purple soil and yellow soil) had no significant differences of artemisinin concentration in cultivated Artemisia annua L. In wild Artemisia annua L, puddy soil and purple soil were significantly superior to yellow soil.
(3) Habitat soil nutrients
Organic matter, available nitrogen, available phosphorus and available potassium were measured. All nutrients above positively correlated with artemisinin concentration.
(4) Regression model between artemisinin concentration and soil nutrients
Artemisinin content, as the dependent variable (Y), fit well regression models like linear stepwise regression, quadratic polynomial stepwise regression and higher degree linear in stepwise regression (a new statistical method by this paper) with soil nutrients (including organic matter, available nitrogen, available phosphorus and available potassium, as the independent variables). All of regression coefficients and path analysis indicated that not only the nutrients but also the nutrient ratios in soil were important to artemisinin concentration. Therefore, when growing Artemisia annua L we had to take account of both nutrient quantity and nutrient balance in soil.
(5) Soil nutrient norm and diagnosis for high quality Artemisia annua L in Chongqing
Sifted out the sampling sites on extreme condition of hydrology and shade and the sampling sites with medium artemisinin concentration, the rest sampling sites were divided into high artemisinin concentration group and low artemisinin concentration group. T-test showed that nutrients (avail N, avail P, avail K) in soil and nutrient ratios (N/P, N/K, P/K) all were high significant differences between the two groups. With reference DRIS method of plant nutrition, the average nutrients (avail N, avail P, avail K) and their ratios (N/P, N/K, P/K) in soils of the high group and confidence limits were presented as norm and diagnosis for high quality production of Artemisia annua L in Chongqing.
3 Comparison and screening of Artemisia annua L germplasm
(1) Character comparisons between germplasm materials
50 germplasm materials from Chongqing and surrounding provinces were grown in field in 2006 under the same water and fertilizer management, most of them had great difference with each other in21 indices of artemisinin concentration, artemisinin yield per plant, biomass, biomass ratio, morphology and growth period. The enormous differences also illustrated the richness of Artemisia annua L resource and proved very essential for germplasm screening.
(2) Germplasm material screening
①Quality-types:6 materials with more than 9.5 g-kg-1 of artemisinin concentration were screened out as super-high-quality-type and7 materials with 8.5～9.5 g-kg-1 of artemisinin concentration as high-quality-type.
②Quality-and-productivity-types:3 materials were screened out as high-quality-and-super-productivity-type (with 8.5～9.5 g-kg-1 and=1.5 g-plant-1 of artemisinin),5 materials as super-quality-and-high-productivity-type(=9.5 g-kg-1 and 1.2～1.5 g-plant-1 of artemisinin),1 material as super-quality-and-medium-productivity-type (=9.5 g-kg-1 and 0.874 g-plant-1 of artemisinin),1 material as medium-quality-and-super-productivity-type (8.062 g-kg-1 and 1.626 g-plant-1 of artemisinin),1 material as inferior-quality-and -super-productivity-type(7 g-kg-1 and 1.58 g·plant-1 of artemisinin).
③Maturity types:The materials were divided into 4 maturity types by growth period:early maturity type, medium maturity type, late maturity type and super late maturity type. Most of the late maturity type materials come from Mountain Wuling area. Their flowering stage almost separated from the other maturity types, which may be the reason of unique character of high quality.
④Other types:Materials in experiment were divided into 3 plant form types of limb type (16%), straightstem type (66%) and tuft type (18%),3 stem colour types of purple, yellow and green, and other types.
(3) Correlation of quality and productivity with main agronomic characters
①Artemisinin concentration had a significantly positive correlation with leaf yield perplant, but no significant correlation with other indices of biomass and biomass ratio, nor with morphological indices (plant height, stem diameter, primary branch number and lenth of the longest primary branch). Among 3 germplasm types of stem colour, purple stem had highest average artemisinin concentration, significantly higher than green stem, and very significantly higher than yellow stem; while there was no significant difference between green stem and yellow stem.
Artemisinin content had a certain positive but no significant correlation with lenth of growth period. Whereas according to 4 maturity types, there were differences. The late maturity type averaged highest, no significant difference with medium maturity type, significantly higher than early maturity type and very significantly higher than super late maturity type.
②Artemisinin yield perplant had a high significant positive correlation with artemisinin concentration, biomass perplant of leaf/stem/branch/aerial part/root/total biomass, high significant positive with plant height, significant with stem diameter and primary branch number, but no significant with any biomass ratio indexes, nor with lenth of the longest primary branch.
Among 3 kinds of plant form types, limb type had the most average artemisinin yield perplant, very significantly more than that of tuft type; straightstem type had the second, but no difference from limb type, nor from tuft type. Among 3 types of stem colour, the purple was high significantly more than the green; the yellow averaged the second, no difference from the purple stem and the green.
Among 4 types of growth period:late maturity type averaged the most of 1.102 g·plant-1, no significant difference with 0.881 g·plant-1 of medium maturity type, significantly more than 0.636 g·plant-1 of early maturity type and very significantly more than 0.380 g·planf'of super late maturity type.
(4) Regression models between main agronomic characters and artemisinin concentration, yield perplant
Regression equations, linear stepwise regression and quadratic polynomial stepwise regression, were established between artemisinin concentration, leaf yield perplant and artemisinin yield perplant respectively with the main agronomic characters (indices of biomass, biomass ratio, morphology and growth period). The models of quadratic polynomial stepwise regression fit better than linear stepwise regression. Regression and path analysis showed that some agronomic characters can to some extent be used as indices for predetermination leaf yield perplant, artemisinin yield perplant, even artemisinin concentration (but low reliability), or to say, for screening germplasm of high-artemisinin-productivity.
4 Effects of application of fertilizer N, P and K and planting density on the growth of Artemisia annua L and the yield of artemisinin
A field experiment with an orthogonal design (L16(45)) was conducted to study the effects of different doses of fertilizer N, P and K and different planting densities on the growth of Artemisia annua L and the yield of artemisinin which provides a scientific basis for the Artemisia annua L cultivation and artemisinin production. The results showed that:
(1) Effects of single factor
Fertilizer nitrogen:nitrogen in moderate supply was advantageous to growth of plant height and stem diameter, but no significant influence on primary branch number; Nitrogen in moderate supply enhanced significantly biomass production (leaf yield and total biomass), leaf N(concentration and accumulation), leaf P(concentration and accumulation), leaf K(concentration and accumulation), artemisinin concentration in leaf and artemisinin yield under both perplant and perplot; Ample N benefited the leaf yield, excess nitrogen had no significant influences on biomass, leaf N and leaf P, but a significant negative effects on leaf K, artemisinin concentration and artemisinin yield. Therefore, contol amount of nitrogen application was essential for growth of Artemisia annua L and artemisinin production. The optimal nitrogen application was urea 650(N300) kg·hm-2.
Fertilizer phosphorus:Phosphorus application increased plant height, stem diameter, primary branch number, leaf yield, total biomass, leaf N(concentration and accumulation), leaf P(concentration and accumulation), leaf K(concentration and accumulation), artemisinin concentration in leaf and artemisinin yield; High level supply of phosphorus showed no significant further positive nor negative effects. Therefore, maximization of artemisinin concentration in leaf and artemisinin yield required phosphorus amount of over 1250 (P2O5150) kg·hm-2. In consideration of efficiency, the suitable amount of phosphorus application was calcium superphosphate1250～2500 (P2O5150～300) kg-hm-2.
Fertilizer potassium:Potassium application had significant effects on increases of plant height and stem diameter, but no significant influence on primary branch number; Inreases in potassium supply dereased leaf N concentration and leaf P concentration, however, increased leaf K(concentration and accumulation), leaf N accumulation and leaf P accumulation. As phosphorus did, potassium application increased leaf yield, total biomass, artemisinin concentration in leaf and artemisinin yield, and over amount potassium showed no significant infulences on biomass and artemisinin. Potassium had a more effective increase on artemisinin concentration than phosphorus did. Therefore, in consideration of comprehensive efficiencies, the suitable amount of potassium application was potassium chloride 350 (K2O 210) kg-hm-2.
Planting density:With increases of planting density, plant height decreased slightly and primary branch number showed no change, and stem diameter and biomass perplant (leaf and total) decreased successively. Moderate increases of planting density increased biomass per plot (group biomass of leaf and total). High density decreased leaf N concentration and leaf P concentration slightly; over crowded density significantly decreased artemisinin concentration and artemisinin yield (both perplant and perplot). By the artemisinin yield per plot, the optimal planting density was 25000 plant9hm-2
(2) Multiple comparisons of treatments
16 treatments in the experiment differentiated greatly from each other in 20 indices of morphology, biomass, leaf nutrition and artemisinin concentration and yield. Among them, leaf yield perplant/perplot varied 2.12/2.76 times, artemisinin concentration variedl.2 times, artemisinin yield perplant/perplot varied 2.3/3.2 times. So it's necessary to evaluate and select the optimal combination of treatment.
(3) Optimization of fertilizer N, P and K and planting density
The ultimate indexes for optimization of fertilizer N, P and K and planting density are artemisinin yield in population (per plot) and artemisinin concentration.
According to multiple comparisons of treatments, the optimization was treatment12(N3P4K2density3:it means N300 kg-hm-2, P2O5450 kg-hm-2, K2O 105 kg-hm-2 and density 25000 plant·hm-2), which can get yield of 36.42 kg·hm-2 with higher artemisinin concentration.
According to effects of single factor, the optimization (the combination of optimal single-factors) should be N300 (urea 650) kg-hm-2, P2O5150～300(calcium superphosphate1250～2500) kg-hm-2, K2O 210(potassium chloride 350) kg·hm-2 and 25000 plant·hm-2 of planting density. The optimization was not any of 16 treatments in this experiment, its combination effects and artemisinin productivity need a further test.
Therefore, a further comparative test need to evalue above. After this, the optimizations can be put into practice in Chongqing.
(4) Correlation of artemisinin concentration and yield with morphology and leaf nutritions (N, P and K)
Artemisinin concentration had a high significantly positive correlation with concentration of leaf K, but no significant correlation with that of leaf N and leaf P; a high significantly positive correlation with stem diameter; a positive correlation with leaf yield perplant and total biomass perplant in relatively high extent.
Artemisinin yield perplant had a significantly positive correlation with concentration of leafN and leaf K, and a positive correlation with leaf P concentration in relatively high extent (p=0.072).
Artemisinin yield per plot had a significantly positive correlation with concentration of leaf N, but no significant correlation with that of leaf P and leaf K.
(5) Linear stepwise regression of leaf yield, artemisinin concentration and yield with morphology and leaf nutritions (N, P and K)
Indexes of morphology and leaf nutritions as the independent variables:
①Leaf yield perplant=-158.46+152.6·stem diameter+5.737·leaf N concentration-32.80·leaf P concentration-5.559'leaf K concentration (R-=0.9576, p=0.0000).
②When adjusting correlation coefficient reached maximum:artemisinin concentration=8.404325+0.844350·stem diameter-0.0629605·primary branch number +0.0824598·leaf K concentration (R2=0.8471, p=0.0000). When all regression coefficients satisfy the significant level (p=0.05):Artemisinin concentration=5.2187+ 0.1108·leaf K concentration (R2=0.7875, p=0.0000).
③Artemisinin yield perplant=1.2111-0.01845·primary branch number+0.1129·leaf N accumulation perplant+0.1528·leaf K accumulation perplant (R2=0.9909, p=0.0000).
④Artemisinin yield per plot=24.5481-0.9067·leaf N concentration+0.2272·leaf N accumulation perplot+0.2498·leaf K concentration+0.4517·leaf K accumulation perplant (R2=0.9915, p=0.0000).
Significance test, determination coefficient and Durbin-Watson statistic of the regressions showed that equations above were good and valid. The regressions and their path analyses proved that leaf N and leaf P (especially leaf N) important to leaf yield and leaf K important to artemisinin concentration.
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