毛薯的营养成分分析和聚类分析

为选育出优良的毛薯种质,本研究以海南大学薯蓣种质资源圃里的80份毛薯为材料,以河南焦作温县的垆土铁棍山药为对照,采用苯酚硫酸法、考马斯亮蓝法以及蒽酮比色法对其干物质、粗多糖、蛋白、可溶性糖和淀粉含量进行测定和比较分析。结果表明:毛薯的干物质含量介于18.62%~38.88%,粗多糖含量介于2.88%~15.82%、蛋白含量介于5.14%~10.71%、可溶性糖含量介于0.1%~13.84%、淀粉含量介于11.94%~64.28%。与对照山药相比,Ds96所测品质均优于对照,可优先选择推广。此外,毛薯各营养品质之间存在着一定的相关性,干物质与糖类存在显著负相关,与蛋白和淀粉表现为正相关。通过对80份毛薯的营养品质进行聚类分析,在欧式距离为3.17时,可将其分为八类,按类群来看,类群Ⅳ各营养价值适中,其他类群在某些营养上比较优秀,可根据需要进行优良资源选择。      

绵羊心脏脂肪酸结合蛋白基因单核苷酸多态性分析

试验旨在探讨心脏脂肪酸结合蛋白（heart fatty acid-binding protein，H-FABP）基因在绵羊中的遗传多态性，并寻找可用于辅助选择的分子标记。本研究以滩羊（250只）及滩羊×湖羊杂交F1代（174只）为试验动物，利用SNaPshot分型技术对H-FABP基因（GenBank登录号：AY157617）的多态位点进行单核苷酸多态性（SNP）分析，统计基因频率和基因型频率，进行Hardy-Weinberg平衡性检测，计算期望杂合度（He）、多态信息含量（PIC）和有效等位基因数（Ne）等遗传多态指标，分析候选基因不同基因型与体重、体长、体高、胸围、胸深、胸宽和管围等生长性状的关联性。结果显示：①检测到9个多态位点：939[A/G]、980[G/A]、1018[T/C]、2878[C/T]、2956[C/T]、3017[G/A]、3341[G/C]、3394[T/A]、1056[-/G]，其中有6处转换、2处颠换、1处单碱基插入。②939[A/G]、980[G/A]、2956[C/T]、3341[G/C]、3394[T/A]和1018[T/C]的He为0.3200~0.4666，PIC为0.2688~0.3577；2878[C/T]、3017[G/A]位点的He为0.0283~0.1272，PIC为0.0279~0.1191，为低度多态；1056[-/G]位点的He在滩羊、滩羊×湖羊杂交F1代群体中分别为0.0120和0，PIC在滩羊、滩羊×湖羊杂交F1代群体中分别为0.0119和0；9个多态位点在滩羊、滩羊×湖羊杂交F1代群体中均符合Hardy-Weinberg平衡定律。③5个多态位点：939[A/G]、980[G/A]、2956[C/T]、3341[G/C]、3394[T/A]处于紧密连锁（D'>0.99），将H-FABP基因分为3个单倍型：AA、AB和BB。④在41只滩羊×湖羊杂交F1代羊中，BB单倍型在各生产性状上具有最大值，但各单倍型间差异不显著（P>0.05）。结果表明，绵羊H-FABP基因具有丰富的遗传多态性，939[A/G]、980[G/A]、2956[C/T]、3341[G/C]、3394[T/A]5个位点紧密连锁，BB单倍型可能是与绵羊生产性状相关的优势单倍型。     

中国地方绵羊群体TYRP1基因遗传变异研究

本研究旨在了解酪氨酸酶相关蛋白1（tyrosinase related protein 1，TYRP1）基因在中国地方绵羊群体内的遗传变异，以及TYRP1基因突变与不同毛色表型绵羊群体的相关性。通过直接测序法和PCR-RFLP技术对10个中国地方绵羊群体进行单核苷酸多态性（SNP）检测，利用Beagle、PLINK和POPGENE等软件对突变位点数据进行单倍型构建、连锁不平衡分析和遗传变异研究。突变位点检测结果表明，在绵羊TYRP1基因内识别了13个SNPs，其中位于TYRP1基因外显子上的10个SNPs位点，除个别位点在大尾寒羊、中国美利奴羊和岷县黑裘皮羊中没有发生突变外，其他突变位点在所有绵羊品种中均出现不同程度变异，说明中国地方绵羊群体具有较高的遗传多样性。单倍型分析结果表明，所有样本中共有42个单倍型，优势单倍型0000000000（245/918）、0100000001（91/918）在所有绵羊群体中均存在，除单倍型0101100000（93/918）在中国美利奴羊中没有出现，单倍型0001000001（69/918）在岷县黑裘皮羊、哈萨克羊群体中没有出现外，在其他群体中均存在。连锁分析结果表明，10个SNPs在所有样本中均存在2个连锁模块。群体遗传变异分析表明，中国地方绵羊群体具有较高水平的群体内遗传变异，各绵羊品种间存在明显的遗传分化模式，且各品种遗传关系与其品种传统分类结果基本一致。本研究为进一步研究TYRP1基因对绵羊毛色遗传性状的影响提供了参考依据。     

Exogenous application of allelopathic water extracts helps improving tolerance against terminal heat and drought stresses in bread wheat (Triticum aestivum L. Em. Thell.)

The allelopathic water extracts (AWEs) may help improve the tolerance of crop plants against abiotic stresses owing to the presence of the secondary metabolites (i.e., allelochemicals). We conducted four independent experiments to evaluate the influence of exogenous application of AWEs (applied through seed priming or foliage spray) in improving the terminal heat and drought tolerance in bread wheat. In all the experiments, two wheat cultivars, viz. Mairaj‐2008 (drought and heat tolerant) and Faisalabad‐2008 (drought and heat sensitive), were raised in pots. Both wheat cultivars were raised under ambient conditions in the wire house till leaf boot stage (booting) by maintaining the pots at 75% water‐holding capacity (WHC). Then, managed drought and heat stresses were imposed by maintaining the pots at 35% WHC, or shifting the pots inside the glass canopies (at 75% WHC), at booting, anthesis and the grain filling stages. Drought stress reduced the grain yield of wheat by 39%–49%. Foliar application of AWEs improved the grain yield of wheat by 26%–31%, while seed priming with AWEs improved the grain yield by 18%–26%, respectively, than drought stress. Terminal heat stress reduced the grain yield of wheat by 38%. Seed priming with AWEs improved the grain yield by 21%–27%; while foliar application of AWEs improved the grain yield by 25%–29% than the heat stress treatment. In conclusion, the exogenous application of AWEs improved the stay green, accumulation of proline, soluble phenolics and glycine betaine, which helped to stabilize the biological membranes and improved the tolerance against terminal drought and heat stresses.     

Performance and uncertainty analysis of a short-term climate reconstruction based on multi-source data in the Tianshan Mountains region,China

Short-term climate reconstruction, i.e., the reproduction of short-term(several decades) historical climatic time series based on the relationship between observed data and available longer-term reference data in a certain area, can extend the length of climatic time series and offset the shortage of observations. This can be used to assess regional climate change over a much longer time scale. Based on monthly grid climate data from a Coupled Model Inter-comparison Project phase 5(CMIP5) dataset for the period of 1850–2000, the Climatic Research Unit(CRU) dataset for the period of 1901–2000 and the observed data from 53 meteorological stations located in the Tianshan Mountains region(TMR) of China during the period of 1961–2011, we calibrated and validated monthly average temperature(MAT) and monthly accumulated precipitation(MAP) in the TMR using the delta, physical scaling(SP) and artificial neural network(ANN) methods. Performance and uncertainty during the calibration(1971–1999) and verification(1961–1970) periods were assessed and compared using traditional performance indices and a revised set pair analysis(RSPA) method. The calibration and verification processes were subjected to various sources of uncertainty due to the influence of different reconstructed variables, different data sources, and/or different methods used. According to traditional performance indices, both the CRU and CMIP5 datasets resulted in satisfactory calibrated and verified MAT time series at 53 meteorological stations and MAP time series at 20 meteorological stations using the delta and SP methods for the period of 1961–1999. However, the results differed from those obtained by the RSPA method. This showed that the CRU dataset produced a low degree of uncertainty(positive connection degree) during the calibration and verification of MAT using the delta and SP methods compared to the CMIP5 dataset. Overall, the calibrated and verified MAP had a high degree of uncertainty(negative connection degree) regardless of the dataset or reconstruction method used. Therefore, the reconstructed time series of MAT for the period of 1850(or 1901)–1960 based on the CRU and CMIP5 datasets using the delta and SP methods could be used for further study. The results of this study will be useful for short-term(several decades) regional climate reconstruction and longer-term(100 a or more) assessments of regional climate change.     

1966-2017年贵州省降雨侵蚀力的时空分布特征

[目的] 分析贵州省1966—2017年降雨侵蚀力R值的时空演变规律，为评估该地区降雨对土壤侵蚀的防治、制定水土保持措施及农业生产规划提供参考。[方法] 基于贵州省33个气象站点1966—2017年的日降雨资料，利用克里金插值法、经验正交函数（EOF）方法、Mann-Kendall检验、Morlet小波分析法等，对贵州省52 a的降雨侵蚀力R值的时空特征进行了分析。[结果] ①EOF分析方法可以较好地解释降水侵蚀力的时空分布特征，其前两个特征向量累计贡献率达52%，揭示了贵州省降雨侵蚀力全局型和东西反向型两种典型的分布模态。分析特征向量所对应的时间系数可得，贵州省的降水侵蚀力主要表现为全省全年偏大、全省全年偏小、东大西小、东小西大4种类型；②贵州省降雨侵蚀力R值年内主要受汛期降雨影响，全省各县市汛期降雨侵蚀力R值均占全年总量的60%以上；③在年际变化上，降雨侵蚀力R值存在多突变的现象，1971—1981年突变频率最为频繁。通过周期检验发现其变化主周期为28 a，次周期分别为12 a和6 a。[结论] 贵州省降雨侵蚀力的时空分布与降雨量的时空分布趋势近似，整体呈现南部大北部小，夏季大冬季小的趋势，在未来几年内降雨侵蚀力R值有上升的趋势。     

基于USLE模型的长株潭城市群生态绿心区水土流失研究

[目的]研究2018年长株潭(长沙市—株州市—湘潭市)城市群生态绿心区最佳植被覆盖和水土流失状况,为区域综合治理提供理论依据。[方法]运用GIS和RS技术,以长株潭区域降雨、土壤、地形、土地利用等数据为基础,采用归一化植被指数(NDVI)模型和USLE国际通用土壤流失方程为优选模型。[结果]长株潭绿心区总面积为52 287 hm~2,整体植被状况较好,高覆盖度(75%～100%)面积最大,占绿心区总面积一半以上,为26 598.40 hm~2;中低覆盖度(30%～40%)面积最小,占区域总面积的8.61%,为4 501.91 hm~2。长株潭城市群生态绿心区总侵蚀(不含微度)面积为3 654.24 hm~2,占总面积的6.99%。湘潭市侵蚀比重最高,为8.51%,长沙市次之,为6.67%,株洲市侵蚀总比例最小,为5.68%。工程建设用地在禁止开发区、限制开发区和控制建设区的侵蚀面积分别为963.92,310.74,735.11 hm~2。[结论]受人为因素、城市建设、产业分布等影响,长株潭城市群生态绿心区覆盖度空间呈现西部低,中东部高的格局,工程建设是造成绿心区土壤侵蚀的主要原因。     

Screening of diverse cassava genotypes based on nitrogen uptake efficiency and yield

As one of the top three tuber crops of the world, cassava is a staple food and feed crop for tropical and subtropical regions. Because of its high drought resistance and tolerance to nutrient deficiency, cassava is usually cultivated on hilly areas that are nutrient-poor. Nitrogen(N) is one of the significant factors affecting cassava yield. A double factorial(N level×genotypes) split-plot field experiment was conducted to analyze differences in yield and N accumulation of 25 cassava genotypes under low-N conditions to screen for cassava genotypes with high-N efficiency. The two-year field experiment showed that cassava yield and N accumulation are determined by specific genotypes, soil N levels, and year. Among these factors, soil N levels are the main factors that are responsible for differences in cassava yield. When yield and relative N accumulation under low-N conditions were used as screening markers, we identified an efficient and responsive genotype(SC10), and two inefficient and non-responsive genotypes(SC205 and GR5). The efficient and responsive genotype and the inefficient and non-responsive genotype can be used as study materials to further reveal the mechanisms for high-N efficiency in cassava.     

龙须菜细胞壁多糖对硼的吸附性能研究

为研究龙须菜(Gracilaria lemaneiformis)细胞壁多糖对硼的吸附作用机制及官能团之间的交互作用,本试验分别采用电感耦合等离子发射光谱(ICP-OES)和傅里叶变换红外光谱(FTIR)技术对其细胞壁多糖组分在吸附试验中进行硼的测定和表征。结果表明,细胞壁去琼胶后,硼吸附量减少50.13%,半纤维素去除后,硼吸附量减少21.20%,故可得纤维素吸附量占细胞壁总硼吸附量的28.67%。同时,通过细胞壁不同组分脱硼及硼胁迫后的红外光谱表征结果可知,龙须菜细胞壁及多糖在吸附硼的过程中,羟基、羧基、多糖碳链C-C为硼离子的主要结合位点,其中,琼胶、半纤维素中起主要作用的官能团为羟基、羧基,纤维素中起主要作用的官能团为多糖碳链C-C。本研究结果为进一步探究龙须菜多糖组分与硼的内在结合机制提供了基础依据。     

超高效液相色谱-串联质谱法测定牛奶和奶粉中五种苯并咪唑类药物

为建立牛奶及奶粉中5种苯并咪唑类药物(阿苯达唑、芬苯达唑、奥芬达唑、噻苯达唑、苯硫氨酯)简便、准确的分析检测方法,以固相萃取为净化手段,采用Acquity UPLC^® BEH C₁₈(100 mm×2.1 mm,1.7 μm)色谱柱进行分离,电喷雾离子源(ESI⁺),多反应监测(MRM)模式检测。结果表明,5种苯并咪唑类药物在1~500 μg·L^-1范围内呈线性相关,相关系数(r)均大于0.996,加标平均回收率介于91.7%~97.8%之间,相对标准偏差(RSD)在1.4%~6.5%之间,基质效应均小于15%。5种药物的检出限均在0.1~3 μg·kg^-1范围内,定量限均在0.5~10 μg·kg^-1范围内。该方法操作简单、快速且灵敏度高,重现性好,能够用于牛奶及奶粉5种苯并咪唑类药物的同时测定。