Comparison of Genomic DNA Extraction Methods for Chenopodium quinoa Willd

To rapidly obtain high-quality genomic DNA from Chenopodium quinoa Willd, the genomic DAN in different tissues （leaves, stems and roots） of Chenopodi- um quinoa Willd was extracted by modified CTAB method, SDS method and high- salt Iow-pH method, respectively. The quality and yield of extracted DNA was deter- mined using agarose gel electrophoresis and UV spectrophotometry. At the same time, the PCR-SSR and SSCP molecular detection was also performed. The results showed that the gel test strips, without obvious decomposition, of all the extraction methods were relatively obvious; the genomic DNA yield extracted by modified CTAB method was highest, followed by that by SDS method, and the genomic DNA extracted by high-salt Iow-pH method was lowest： the genomic DNA yields extracted by different methods from Chenopodium quinoa Wiltd leaves were all high- er than those from roots and stems; the quality of Chenopodium quinoa Willd ge- nomic DNA extracted by modified CTAB method and high-salt Iow-pH method was better, and polyphenols, polysaccharides and other impurities were removed more completely. The PCR-SSR and SSCP detection results showed that the genomic DNA extracted by different methods from different tissues of Chenopodium quinoa Willd all could be better amplified, and high-quality strips could be obtained. So the Chenopodium quinoa Willd genomic DNA extracted by the three methods all can be used for subsequent molecular biology research.

Optimization of the Callus Induction System of Chenopodium quinoa Willd

Callus induction effects of nine varieties of Chenopodium quinoa Willd. were compared by taking stem segments and cotyledons of C. quinoa as the ex- plants. At the same time, callus JnductJon of stem segments was optimized, as well as the callus proliferation system. Research results showed that the optimal explant for callus induction was stem segment. The average callus induction rate of nine varieties reached 90% in culture medium MS ＋ 0.5 mg/L 2, 4-D. In the callus opti- mization test, treatment VI （MS ＋ 0.5 mg/L 2, 4-D ＋ 0.5 mg/L KT ＋ 0.5 mg/L NAA） and treatment II （MS ＋ 0.5 mg/L 2, 4-D） had close induction rate, but the callus morphology was greatly different. The latter had loose, glossy and yellowish white calluses. Therefore, culture medium MS ＋ 0.5 mg/L 2, 4-D was the optimal for callus induction. And using 2, 4-D together with KT and NAA could significantly increase the proliferation rate of calluses.

Present Situations and Suggestions for Large-scale Development of Chenopodium quinoa Willd.

In this paper,based on the study of Chenopodium quinoa Willd.planting,it is concluded that the current situations of large-scale development of C.quinoa Willd.include the following four aspects:first,the research on C.quinoa Willd.varieties needs to be strengthened;second,it is insufficient to master the training environment and cultivation techniques;third,the large-scale planting of C.quinoa Willd.is not enough;fourth,the degree of mechanization of C.quinoa Willd.planting is not enough.In view of the above situation,this paper puts forward the following effective suggestions to strengthen the large-scale development of C.quinoa Willd.:the first is to increase the investment in C.quinoa Willd.variety research;the second is to strengthen the analysis of introduction and screening of C.quinoa Willd.varieties;the third is to study the best planting environment and cultivation techniques of C.quinoa Willd.;the fourth is to increase the scale of mechanized production of C.quinoa Willd.;the fifth is to increase the research and development of C.quinoa Willd.related products and their deep processing technology.

Rapid Detection of Fat Content in Chenopodium quinoa Willd by Near Infrared Spectroscopy

This study was conducted to find a method for rapid determination of fat content in complete quinoa （ Chenopodium quinoa Willd） seeds. The near infrared spectra of 100 quinoa samples were collected, and a mathematic model was built using the near infrared spectra, so as to perform prediction. The results showed that within the wavelength range of 1 0 000-4 000 cm ^-1 , the quantification model of fat content built by first derivative ＋vector normalization spectral pre-processing had better calibration and prediction effects, and showed a determination coefficient of cross validation （ r cv^ 2 ） of 0.939 3 and a determination coefficient of validation （ rval^2 ） of 0.923 5. The near infrared spectral model of fat could be used for rapid detection of fat contents in quinoa.

Rapid Detection of Starch Content in Quinoa(Chenopodium quinoa Willd.)by Near Infrared Spectroscopy

This study was conducted to establish a method for rapid determination of crude starch content in complete quinoa （ Chenopodium quinoa Willd） seeds. The near infrared spectra of 100 quinoa samples were collected, and a mathematic model was built using the near infrared spectra within the wavelength range of 1 0 000-4 000 cm^-1 by first derivative ＋vector normalization spectral pre-processing. The results showed that the quantification model of starch content had better calibration and prediction effects, and showed a determination coefficient of cross validation （ r^2 cv ） of 0.914 7 and a determination coefficient of validation （ r^2 val ） of 0.903 1. The determination of starch content in complete quinoa seeds by near infrared spectroscopy is totally feasible.

Rapid Detection on Quinoa Fiber Based on Near Infrared Spectroscopy

[Objective] To explore a rapid determination method for fiber content in grains of quinoa. [Method] Near infrared spectra of 100 quinoa samples were collected. The predicted models for quantitative analysis of fiber contents in the grains were built using near infrared transmittance spectroscopy （NITS）. [Result] In the wavelength range of 10 000-4 000 cm-1, the near infrared quantitative model of quinoa crude fiber was set up via first derivative ＋ vector normalization preprocessing and combining with the data from chemical methods. The calibration and prediction effect were best, and then the cross validation determination coefficient （FFcv） and external validation determination coefficient （FFval） of fiber by near in- frared quantitative model were 0.884 8 and 0.876 1, respectively. [Conclusion] the model of NITS about complete grains quinoa fiber can be available for fast detecting quinoa fiber content.

36份藜麦种质资源苗期耐盐碱性评价与筛选

为探究不同藜麦种质苗期耐盐碱性差异,本研究对36份藜麦种质苗期用150 mmol/L盐碱浓度(NaCl∶NaHCO_(3)=4∶1)进行胁迫处理,对株高、叶面积和叶片相对含水量等11个指标进行了测定,采用主成分分析等多种统计方法,筛选出适宜山西地区生长的藜麦种质。结果表明,盐碱胁迫下,藜麦种质各类指标相互之间均存在一定程度的关联;本试验中共提取5个主成分因子,方差累积贡献率为74.947%,可以代替11个指标的绝大部分信息,显示盐碱胁迫下藜麦苗期的抗盐碱特性,并且计算出耐盐碱性综合评价D值,并基于D值进行聚类分析,将36份种质资源分为四个大类,包括高耐盐碱种质5份、耐盐碱种质14份、弱耐盐种质11份、盐碱敏感种质共6份。

高原藜米(Chenopodium quinoa Willd.)单基因性状的异源四倍体分离现象

高原藜米(Chenopodium quinoa Willd.)是一个异源四倍体作物,但有些研究报道该作物在单个基因位点上的分离行为有二倍体分离特征。本研究在多年观察试验的基础上,2011-2012年两年在西藏不同海拔(南木林县:海拔4 000 m;林芝:海拔2 800 m)条件下对雄性不育植株进行杂交所得的F1和F2代中分离产生了3种不同的单基因控制的性状特征进行了较大群体的观测试验。等位基因分离分析结果显示,在F1和F2的分离范围内出现了二体双基因和四体的遗传性状,在F2代减数分裂中出现的一定比例的畸变现象也显示了其不定的多价体形态,这些结果都表明了藜米的异源四倍体特征。这一特征产生的根本原因是某些基因位点重复和至少在有些同源染色体之间发生了联会现象。本研究发现,藜米某些基因位点发生的四倍体分离现象可能导致了藜米育种和遗传研究中的复杂性,对于指导该作物育种或生产都有一定的实际意义。四倍体分离,特别是其飘忽不定的现象,可能会使将来藜米基因图谱研究分析变的更加复杂,这一点在今后的研究中应给予足够的重视。

昆诺阿藜(Chenopodium quinoa Willd)萌发期耐盐性测定

本试验对早熟昆诺阿藜和晚熟昆诺阿藜萌发期的耐盐性进行了测定。经多种测验,结果表明这2个品种的昆诺阿藜在萌发期均具有较强的耐盐性。通过与沙打旺和草原1号苜蓿的对比试验,表明其耐盐性强弱依次为晚熟昆诺阿藜>早熟昆诺阿藜>沙打旺>草原1号苜蓿。

农田土壤根际微生物群落多样性特征研究

以藜麦、蚕豆、油菜和马铃薯为供试材料,设置连作藜麦(HLMA)和藜麦轮作马铃薯(HLMLS)、油菜(HLYC)、蚕豆(HLCD)4种不同种植模式,通过测定土壤养分含量,并利用高通量测序技术(Illumina-HiSeq)对4种种植模式下藜麦根际土壤的基因组进行测序,研究不同种植模式对作物土壤养分和细菌群落组成特征的影响。结果表明:3种轮作种植模式下全钾、碱解氮、速效磷、速效钾含量和pH较连作种植模式显著下降。HLCD模式提高土壤细菌群落丰富度指数、多样性指数和优势度指数。细菌组成研究结果显示,4种种植模式下占优势的细菌均为放线菌门(Actinobacteria)、变形菌门(Proteobacteria)、酸杆菌门(Acidobacteria)、绿弯菌门(Chloroflexi)、拟杆菌门(Bacteroidetes)和芽单胞菌门(Gemmatimonadetes)。HLCD处理下,放线菌门(Actinobacteria)、酸杆菌门(Acidobacteria)、绿弯菌门(Chloroflexi)、拟杆菌门(Bacteroidetes)和芽单胞菌门(Gemmatimonadetes)相对丰度均显著高于其他处理,分别达到50.48%、13.17%、11.90%、7.42%和4.50%,较HLMA处理分别增加44.21%、56.36%、36.19%、224.24%和53.16%。土壤细菌群落优势属以Subgroup、芽球菌属(Blastococcus)、67-14和土壤红杆菌属(Solirubrobacter)为主,但不同种植模式所占土壤各细菌属的相对丰度大小存在差异。HLCD处理下,Subgroup、芽球菌属(Blastococcus)、67-14和土壤红杆菌属(Solirubrobacter)相对丰度均显著高于其他处理,分别达到7.08%、5.48%、4.35%和3.49%,较HLMA处理分别增加51.99%、64.86%、49.89%和71.85%。聚类分析显示HLYC和HLMLS的组成最接近,其次是HLCD,HLMA的组成与前两者相差较大。土壤全钾、有效氮和速效磷是土壤细菌群落优势菌门变化的驱动因素。综上所述,连作藜麦后轮作蚕豆、油菜和马铃薯可改善土壤肥力,提高细菌群落组成丰富度。

藜麦水溶蛋白的提取工艺优化及其酶解多肽抗氧化活性研究

目的优化复合酶协同超声辅助法提取藜麦水溶蛋白的工艺,探讨7种商业蛋白酶对藜麦多肽的抗氧化活性的影响。方法采用Box-Behnken响应面法,对超声辅助糖化酶-纤维素酶复合酶法提取藜麦水溶蛋白的工艺进行优化。使用碱性蛋白酶、菠萝蛋白酶、风味蛋白酶、木瓜蛋白酶、酸性蛋白酶、胰蛋白酶和胃蛋白酶制备藜麦多肽,通过1,1-二苯基-2-三硝基苯肼(1,1-diphenyl-2-picrylhydrazyl,DPPH)法和2,2’-联氮二(3-乙基-苯并噻唑-6-磺酸)二铵盐[2,2’-azinobis(3-ethylbenzothiazoline-6-sulfonic acid)ammonium salt,ABTS]法对其抗氧化活性进行探究。结果通过响应面模型对复合酶超声辅助提取条件进行优化,得到最佳提取条件为:总加酶量400 U/g、pH 5.0、时间60 min。在此条件下,藜麦水溶蛋白的提取率为75.09 mg/g。藜麦水溶蛋白在木瓜蛋白酶酶解4 h获得的藜麦多肽抗氧化活性最佳,DPPH自由基和ABTS阳离子自由基清除率分别为79.64%和76.14%。结论采用响应面法优化复合酶辅助超声法提取藜麦蛋白的工艺优化方法可行;藜麦蛋白水解物具有较好的抗氧化活性,为藜麦作为功能食品深入开发提供依据。

藜麦开花期干旱胁迫对其形态特征及生理特性的影响

为探究干旱胁迫对开花期藜麦形态特征的影响,以陇藜1号、青藜1号两个藜麦品种为试验材料,以正常灌溉为对照,设置3个干旱胁迫强度处理,在藜麦开花期进行干旱胁迫15 d后,测定各处理植株叶片相对含水量、叶比重、过氧化氢酶(CAT)活性、丙二醛(MDA)含量等生理指标,干旱胁迫15 d后恢复正常灌水,成熟时测定植株高度、主穗长和有效分枝数。结果表明,植株叶片相对含水量和叶比重随土壤水分的降低而下降,不同程度干旱胁迫处理对叶片相对含水量影响差异不显著,但对叶比重影响显著;MDA含量、CAT活性也与干旱胁迫程度呈正相关,即随干旱胁迫强度的加重而上升。干旱胁迫处理后,植株高度、主穗长和有效分枝数下降,但轻度和中度干旱胁迫对株高、主穗长度影响差异不显著,重度干旱胁迫显著影响株高和主穗长,中度和重度干旱胁迫显著影响有效分枝数。说明开花期适度干旱胁迫对藜麦形态特征影响不大。

藜麦在张家口地区试种的表现与评价

本研究对在张家口地区进行试种的4份藜麦材料进行了农艺性状与品质性状评价。试种藜麦株高范围为119．27～180．51cm，生育期范围为103～118d。子粒饱满，产量可达3637．32kg／hm2，蛋白质含量为14．79±0．72％，脂肪含量为7．57±1．17％，天冬氨酸、赖氨酸和精氨酸含量分别为1．37±0．06％、1．00±0．03％、1．47±0．08％，皂苷含量为2．12±0．50％。以上结果与文献对比结果表明，藜麦富含多种营养成分，且蛋白质含量丰富、氨基酸比例平衡、增产潜力大等特点能够充分表现，适宜在张家口地区以及生态条件类似的地区种植。

利用SSR标记分析藜麦品种的遗传多样性

为了解藜麦种质资源的多样性,本研究利用SSR引物对所搜集的41个藜麦种质的多态性及其亲缘关系进行了分析。结果表明,从54对SSR引物中筛选出了16对能明显扩增出稳定的多态性条带的引物,共检测出139个等位基因条带,每一对引物的等位基因个数为3~13,平均为8.7;16对引物的多态信息含量（PIC）变幅为0.208~0.432,平均为0.366。UPGMA聚类分析显示,41份材料的遗传相似系数（GS）在0.374~0.906之间,平均相似系数为0.626。在阀值（GS）约为0.665时,41份材料可分为4大类。其中614929与B.B.Quinoa浙Ⅰ间的遗传相似系数最小,为0.374,表明来源于不同地区的遗传距离较远,遗传基础较广泛。藜麦品种资源间的亲缘关系的揭示为藜麦资源保存和新品种选育提供了理论依据。

生物菌肥与无机肥配施对藜麦农艺性状、产量性状及品质的影响

为探索适宜晋北地区推广应用的藜麦栽培管理模式,实现藜麦产量和品质提升,本试验选用当地自有品种华青1号,采用单因素完全随机设计,以有机肥和无机肥配施比例为变量,设常规施肥CK(有机肥0 kg hm^(-2),尿素和磷酸二胺各450 kg hm^(-2))、有机肥和无机肥配施比例T1(有机肥1500 kg hm^(-2),尿素和磷酸二胺各225 kg hm^(-2))、T2(有机肥2250 kg hm^(-2),尿素和磷酸二胺各225 kg hm^(-2))、T3(有机肥3000 kg hm^(-2),尿素和磷酸二胺各225 kg hm^(-2))4个处理,分析藜麦生育进程、农艺性状的差异,揭示藜麦产量和品质同步提升的农学性状,探求藜麦高产优质适宜的有机无机配施比例。结果表明,生物菌肥与无机肥配施可增加土壤表层有机质含量,降低碱解氮和有效磷含量及土壤pH,显著增加速效钾含量,且随生物菌肥施用量的增加,土壤中有机质、碱解氮、有效磷和速效钾含量提高,pH降低;与常规施肥CK相比,配施生物菌肥能够缩短藜麦生育期,提高成熟期藜麦株高、茎秆直径和茎秆强度,从而降低倒伏率;增加藜麦分枝数、千粒重,提高了产量;可增加蛋白质和脂肪含量,T2处理表现明显;降低淀粉含量,以T2处理最低,但与其他两处理间差异不显著;生物菌肥与无机肥配施可提高植株对肥料的利用,随生物菌肥施用量的增加,氮肥利用效率、磷肥利用效率及氮磷肥偏生产力先升后降,均以T2处理最高。相关分析结果表明,藜麦籽粒产量与千粒重的关系最密切,籽粒蛋白质含量与产量、千粒重、分枝数和茎秆强度也呈正相关,籽粒淀粉含量与千粒重呈负相关。因此,本试验条件下,晋北地区有机无机配施量为氮磷肥各225 kg hm^(-2)配施生物有机菌肥2250 kg hm^(-2)时利于藜麦实现产量品质同步提升。

基于近红外光谱法的藜麦脂肪含量快速检测

为了探索一种快速测定完整藜麦（Chenopodium quinoa Willd）子粒脂肪含量的方法,采集100个藜麦样品的近红外光谱,运用近红外光谱法建立数学模型并进行预测。结果表明,在10 000~4 000 cm-1波长范围内,运用一阶导数＋矢量归一化光谱方法进行预处理,结合化学方法所得数据建立藜麦粗脂肪近红外光谱定量模型,校正和预测效果最佳,所得的粗脂肪近红外定量模型的交叉验证决定系数（R2cv）为0.939 3,外部验证决定系数（R2val）为0.9235。建立的脂肪近红外光谱模型,可以用于藜麦脂肪含量的快速检测。

藜麦的主要营养成分、矿物元素及植物化学物质含量测定

以黑色、红色、乳白色3种进口南美藜麦和国产乳黄色藜麦为实验材料,对其所含主要营养素、8种矿物元素(K,Na,Ca,Mg,Fe,Mn,Cu,Zn)和植物化学物质(多酚、黄酮、皂苷)的含量进行测定.结果显示,4种藜麦的营养组成稍有差异;与常见谷物(小麦、稻米、玉米、小米)相比,藜麦中淀粉含量较低,蛋白质、脂肪含量丰富,可以作为膳食纤维、多酚、黄酮物质的良好来源.

基于近红外光谱法快速检测藜麦纤维含量

[目的]探索一种快速测定完整藜麦籽粒纤维含量的方法。[方法]采集100个藜麦样品的近红外光谱,运用近红外光谱分析技术建立数学模型并进行预测。[结果]在10 000~4 000 cm^(-1)波长范围内,运用一阶导数+矢量归一化光谱方法进行预处理,结合化学方法所得数据建立藜麦粗纤维近红外定量模型,校正和预测效果最佳,所得的粗纤维近红外定量模型的交叉验证决定系数为0.884 8,外部验证决定系数为0.876 1。[结论]以完整藜麦籽粒为样品所建立的纤维NITS模型可用于藜麦纤维含量的快速检测。

响应面法优化藜麦麸皮皂苷最佳提取工艺及其α-葡萄糖苷酶抑制活性

采用响应面法优化了藜麦麸皮超声提取皂苷的最佳工艺,并考察了最佳提取工艺条件下提取物对α-葡萄糖苷酶的抑制活性。同时建立酶反应动力学方程对其抑制动力学进行分析,探讨了藜麦麸皮提取物对α-葡萄糖苷酶的抑制机制。实验结果表明,藜麦麸皮超声提取皂苷的最佳工艺条件为液料比15 mL/g,75%乙醇超声提取,超声时间1.5 h,超声温度45℃,在此条件下藜麦麸皮皂苷的提取得率为2.370%±0.022%。α-葡萄糖苷酶抑制活性实验表明提取物的抑制作用明显强于阳性药阿卡波糖(P<0.05),其IC_(50)值为0.620±0.057 mg/mL。酶动力学研究表明藜麦麸皮总皂苷提取物是一种可逆的混合性抑制类型。本研究为明确藜麦麸皮提取物的降低餐后血糖作用机理提供了参考,为藜麦麸皮的开发与利用提供了依据。

响应面法优化藜麦麸皮皂苷酸水解工艺

为了提高藜麦麸皮皂苷的抗氧化性,以DPPH·清除率为指标,对其酸水解工艺条件进行了响应面法优化。结果表明:影响藜麦麸皮皂苷酸水解的因素大小顺序为:水解时间>水解温度>盐酸浓度>液液比,优化的最佳工艺条件为:盐酸浓度4.8 mol/L、液液比1∶2(mL/mL)、水解温度80℃、水解时间2.5 h。此工艺条件下,藜麦麸皮皂苷水解产物对DPPH·的清除率为68.84%,较水解前清除率提高了2倍多。酸水解可有效提高藜麦麸皮皂苷清除自由基及抗氧化活性。