冬小麦(Triticum aestivum)分蘖冗余生态学意义以及减少冗余对水分利用效率的影响

通过盆栽试验,以旱作冬小麦(Triticum aestivum)为材料,分别在拔节和抽穗期对分蘖进行人工干扰,来模拟不可预测的自然干扰,对冬小麦分蘖冗余的生态学意义以及减少这些冗余对水分利用效率影响进行研究.设置3个处理:从拔节期开始剪去所有小的分蘖,仅保留主茎和一个大的分蘖(A);在拔节期剪去主茎和两个大的分蘖,保留所有小的分蘖(B);在孕穗期剪去主茎和有效分蘖,保留无效分蘖(C).没有被干扰的植物作为对照(CK).通过花期测定叶片的叶绿素含量、叶绿素荧光参数、气孔导度和蒸腾速率等生理指标来评价植物的生理与生化活性.结果显示,在拔节期和抽穗期去除主茎和大蘖后,无效分蘖的生理活性被激活,开始执行有效分蘖的功能.到花期时,这些无效分蘖已经在生理活性上满足了补充和替代有效茎的要求.虽然株高和穗的整齐度、穗数和产量显著下降,但并没有防碍小麦的繁衍子代,因此,正是这些由早期"无效分蘖"补充而来的有效茎,避免了小麦绝种的风险.而在拔节期去除无效分蘖后,对小麦产量没有显著影响,但提高了水分利用效率,和对照相比水分利用效率提高了10%.因此,可以认为小麦在分蘖上存在着对水分利用不利的生长冗余,减少这些冗余有望节约用水、提高作物的水分利用效率.     

调亏灌水和分蘖干扰对冬小麦生长的补偿效应

为探索抑制个体功能的生长冗余以实现群体性能优化并挖掘作物高产潜力的途径,通过桶栽试验,选择分蘖能力中等的小偃22号和分蘖能力较强的郑麦7698,对比研究2种灌水模式（全生育期充分灌水和分生育期调亏灌水）和3种分蘖干扰（从拔节期开始去除所有小分蘖,仅保留主茎和1个大分蘖;抽穗期去除所有无效分蘖;以不作任何干扰为对照）,来模拟不同水分供应和不可预测干扰对冬小麦生理生长、产量和水分利用效率的补偿机制.结果表明： 2个冬小麦品种均存在生长冗余.与小偃22号相比,郑麦7698有效分蘖数较高,但穗部性状较差.调亏灌水和抽穗期去除无效分蘖均可减少生长冗余,弱化竞争能力,改变源 库关系,提高资源分配.但冗余消除过度（拔节期干扰）则会破坏植株固有的根冠平衡和功能结构,导致生长的不足补偿.与对照相比,调亏灌水联合抽穗期去除无效分蘖可在时空尺度上充分开发和利用作物自身调控潜力实现补偿生长,在不显著影响籽粒产量的同时可提高水分利用效率20.4%～25.4%,是适宜的减冗增效措施.     

干旱灌区冬小麦根系的生长冗余

采用管栽试验通过人为去除根系的方法对甘肃河西绿洲灌区2个冬小麦品种根系的形态特征及根系与地上部分的关系进行了研究。结果表明:去除根系的冬小麦的前期生长受到一定程度的限制,与对照相比,其根冠比及其它根系指标均有所下降,且根系去除程度越大降低幅度越大;生长后期小麦根系出现了超补偿效应;成熟期,去除1/4根系和去除1/2根系处理的冬小麦无论是主茎还是分蘖的穗长、穗质量、穗粒数、粒质量等均比对照增加;但前者主茎各项指标的增幅较大,而后者分蘖的各项指标增幅较大。初步确定冬小麦在充分灌溉条件下至少有1/4的根系是冗余的。     

施氮量对小麦叶片硝酸还原酶活性、一氧化氮含量和气体交换的影响

研究了不同施氮量对冬小麦分蘖到抽穗期叶片硝酸还原酶(NR)活性、一氧化氮(NO)含量、气体交换参数和籽粒产量的影响.结果表明:叶片光合速率（P_n）、蒸腾速率（T_r）、瞬时水分利用效率（IWUE）和产量均随施氮量的增加呈先升高后降低的趋势,在180 kg·hm^-2氮处理时达到最高.随施氮量的增加,叶片NR活性提高; 在分蘖期和拔节期,叶片NR活性与NO含量呈显著线性相关（R²≥0.68,n=15）,NO含量和气孔导度（G_s）呈显著正二次相关（R²≥0.43,n=15）;低氮处理下,NR活性较低使叶片NO含量维持在较低水平,促进气孔开放,高氮处理下,NR活性较高使叶片NO含量增加,诱导气孔关闭;在抽穗期叶片NR活性和NO含量无显著相关关系,虽然NO含量和G_s也呈显著正二次相关（R²≥0.36,n=15）,但不能通过施氮提高NR活性来影响叶片NO含量,进而调节叶片气孔行为.合理施氮使小麦叶片NO含量维持在较低水平,可提高叶片G_s、T_r和IWUE,增强作物抗旱能力,促进光合作用,提高小麦产量.     

灌水时间对冬小麦生长发育及水肥利用效率的影响

研究秸秆还田后不同越冬前灌水时间(11月10日、11月25日、12月10日)和春季灌水时间(3月5日,返青期;4月5日,拔节期)对冬小麦生长发育、干物质运转及水肥利用效率的影响.结果表明： 越冬前灌水时间主要影响冬前和拔节期群体大小,而春灌时间对冬小麦成穗数、产量、干物质运转和水肥利用效率的影响较大,而且越冬前灌水时间对冬小麦产量构成的影响与春灌时间密切相关.在春季返青期灌水条件下,越冬前灌水时间越早,成穗数和产量越高;在拔节期灌水条件下,随越冬前灌水时间的推迟,成穗数和产量呈先升高再降低的趋势,而穗粒数逐渐增加,千粒重受影响较小.水分利用效率、养分吸收量和肥料利用率均随越冬前灌水时间的推迟而降低,随春季灌水时间的推迟而升高.因此,在秸秆还田足墒播种条件下,将越冬前灌水时间适当提前,可以塌实土壤,促进冬小麦冬前分蘖,增加群体大小;配合拔节期增量灌水,可以控制早春无效分蘖,提高成穗率,稳定粒重,提高水肥利用效率,实现节水高产高效栽培.     

覆膜栽培下春小麦种群的生长冗余与个体大小不整齐性的关系

 增加有效分蘖数被认为是提高小麦(Triticum aestivum)产量的重要方法之一,但是小麦种群在生长进程中也会形成大量的无效分蘖,存在“生长冗余”。研究了覆膜栽培对两个春小麦种群中无效分蘖比率和收获指数的影响,并从植物个体大小不整齐性和生活史策略的种群生态学角度探讨其影响机制。与露地对照相比,覆膜栽培能显著提高春小麦产量(+38.5%);产量的提高源于地上部分生物量（+44.7%）的显著增加。但是, 覆膜种群的繁殖分配（穗重/地上部分生物量,-5.2%）和收获指数(-4.5%)显著降低;在几个主要生     

秸秆还田条件下灌水模式对冬小麦产量和水肥利用效率的影响

于2008-2010年,在山西省临汾市尧都区半干旱、半湿润季风气候区,通过大田试验研究了玉米秸秆连续还田条件下灌水模式对冬小麦籽粒产量、干物质转移及水肥利用效率的影响.结果表明:浇越冬水可促进小麦分蘖;浇拔节水可提高分蘖成穗率,增加成穗数;浇孕穗水可促进穗部干物质积累,提高千粒重.浇2水时,推迟第2次浇水时期使叶片干物质转移量和穗粒数增加;浇2水比浇l水的肥料表观利用率高,可促进穗部干物质积累.越冬水灌水量和总灌水量对分蘖、穗部干物质积累的影响较小;拔节期或孕穗期增加灌水量则更有利于养分吸收及干物质积累与转移,提高籽粒水分利用效率,产量构成因素协调,增产效果明显.因此,确保越冬水可实现稳产,在越冬水基础上,拔节期增量灌水(900 m3·hm-2)可满足冬小麦中后期生长发育的需要,提高籽粒水分利用效率,实现节水高产栽培.     

冬小麦拔节期不同茎蘖对低温胁迫的反应及抗冻性评价

以小麦济南17和山农8355为材料,在低温胁迫条件下,测定了不同茎蘖功能叶和叶鞘超氧化物歧化酶(SOD)、过氧化物酶(POD)、过氧化氢酶(CAT)活性及丙二醛(MDA)和可溶性蛋白含量,并利用主成分分析、聚类分析对其抗冻性进行综合评价.结果表明： 低温胁迫条件下,小麦拔节期不同茎蘖功能叶和叶鞘中SOD、POD和CAT活性均不同程度地上升,MDA和可溶性蛋白含量则不同程度地上升或下降.利用主成分分析和聚类分析,将济南17不同茎蘖分为3类：主茎和一级分蘖Ⅰ、Ⅱ属强抗冻蘖组,一级分蘖Ⅲ、Ⅳ和二级分蘖Ⅰp属中度抗冻蘖组,二级分蘖Ⅱp属弱抗冻蘖组;将山农8355不同茎蘖分为3类：主茎和一级分蘖Ⅰ、Ⅱ、Ⅲ属强抗冻蘖组,一级分蘖Ⅳ和二级分蘖Ⅰp属中度抗冻蘖组,二级分蘖Ⅱp属弱抗冻蘖组.表明冬小麦拔节期不同茎蘖存在抗冻性差异,且低位蘖较高位蘖抗冻.
     

小麦灌水时期与灌水量对花后果聚糖积累与转运及水分利用效率的影响

于2004-2005年和2005-2006年冬小麦生长季,在山东泰安和兖州进行田间试验,研究不同灌水时期和灌水量处理对冬小麦开花后倒二节间果聚糖积累与转运和水分利用效率的影响.结果表明：全生育期不灌水促进了灌浆后期倒二节间贮藏果聚糖向籽粒的转运.在拔节期和开花期各灌水60 mm,可提高开花后旗叶的光合速率和同化物输入籽粒量及其对籽粒的贡献率,拔节期、开花期和灌浆期各灌水60 mm或拔节期和开花期各灌水90 mm,灌浆后期旗叶的光合速率显著降低,营养器官花前贮藏同化物转运量及其对籽粒的贡献率升高,花后同化物输入籽粒量及其对籽粒的贡献率降低,灌浆后期倒二节间的聚合度（DP）≥4、DP=3果聚糖滞留量增加,不利于果聚糖向籽粒的转运.两个生长季中,拔节期和开花期各灌水60mm处理的小麦籽粒产量较高,水分利用效率最高.拔节期、开花期和灌浆期各灌水60 mm或拔节期和开花期各灌水90 mm,小麦籽粒产量无显著变化,水分利用效率降低.     

小麦氮素利用效率的基因型差异

通过土培盆栽试验,研究了130份小麦材料在相同氮素水平下生物量、氮素积累量、氮素生产效率的基因型差异,旨在筛选具有高效利用氮素能力的小麦基因型,为氮高效小麦育种提供种质资源.结果表明:拔节期、抽穗期和成熟期供试小麦单株生物量变幅分别为1.06～3.08 g、1.88～9.05 g和2.64～13.75 g,单株籽粒产量变幅为1.38～9.90 g.拔节期、抽穗期氮素干物质生产效率变幅分别为25.62～65.41 g.g-1 N(F=5.099**)和35.79～88.70 g·g-1 N(F=5.325**),成熟期氮素籽粒生产效率变幅为19.06～38.54 g.g-1 N(F=4.669**).不同氮素生产效率小麦基因型拔节期氮素干物质生产效率(F=637.941**)、抽穗期氮素干物质生产效率(F=201.173**)及成熟期氮素籽粒生产效率(F=443.450**)存在极显著差异.不同氮素生产效率小麦基因型拔节期、抽穗期及成熟期生物量差异显著,有效分蘖数与穗数差异不显著.氮素生产效率高的基因型具有无效分蘖少、抽穗期前氮素利用能力强、抽穗期-成熟期氮素吸收与再利用能力强等特点.典型氮高效基因型小麦省CX...     

Axis formation: redundancy rules

The role of BMP antagonists in the Spemann-Mangold organizer of vertebrate embryos is a controversial issue. A study using combined knock down of multiple antagonists finally reveals dramatic effects.     

Adaptation, redundancy or resilience

Diversity creates resilience both in ecosystems and living organism. Yet, although genetic diversity protects organisms from many diseases and disorders, it also makes it much harder for geneticist to identify the risk factors that lead to common diseases.The study of the natural environment teaches us that ecological systems rich in biodiversity have greater resilience than less diverse systems, and that resource-poor ecosystems tend to have greater biodiversity to buffer against environmental change. The African savannah, a huge ecosystem, contains an abundance of grasses and other plants, herbivores and their predators. The loss of one species might be compensated for by the presence of others, but if species are relentlessly removed, one after another, the continuing loss will weaken the system until it changes its steady state and eventually collapses.To use another illustrative example of the protection conferred by diversity: modern agriculture uses only six cereal crops as the main basic staples of the human diet. If even one crop were threatened—perhaps by a plant virus or other pathogen—the consequences for humanity would probably be catastrophic. To avoid such a scenario, breeders have created hundreds of cultivars, each with minor phenotypic changes that confer resistance to a biotic or abiotic stressor. Thus, humans too create resilience by increasing biodiversity.In order to improve our understanding of complex diseases, we can extend this notion of diverse ecosystems to organisms. Similarly to the disappearance of one species in an ecosystem with abundant biodiversity, the loss of one gene function might not be immediately apparent, because many such changes can be compensated for, at least partly, by changes in other genes. However, a series of small, cumulative changes in many genes could lead to the breakdown of the phenotype of the organism, rendering it less resilient and more susceptible to disease, especially when it is under environmental or infectious stress. It is like throwing a stone in a pond, which generates small waves; throwing many stones at once causes a more complex disturbance, whereby waves combine to create bigger waves or attenuate each other by interference. Thus, even inherited disorders such as hypertrophic cardiomyopathy show several phenotypes as other genes modify the action of the affected gene.Geneticists have found many genes or whole genomic regions that have multiplied throughout the genome by duplication (Eisenstein, 2010). The repeated sequences might be identical, nearly identical or related, and they can be functional or non-functional, as is the case with pseudogenes. In terms of diversity, repeats have apparently given rise to multigene families, such as the collagens, which encode several structural proteins. Even microorganisms, such as Mycobacterium tuberculosis, have extended gene families or several insertions.It was assumed previously that pseudogenes are unnecessary gene copies and therefore inactivated. Yet, there is increasing evidence that they perform a regulatory role, by influencing the function of the parent gene. The variation in copy number also seems to be as, or even more, important than the number of polymorphisms, particularly in complex diseases or phenotypic traits. One negative example is the gene that codes for glutathione transferase, GSTM1. Roughly half of the population carries a deletion of GSTM1, which reduces their ability to neutralize isothiocyanates. Clearly then, many individuals will have two null alleles and an increased risk of xenobiotic-induced disease. Another fascinating example is that preference for a high-starch diet is associated with multiple copies of the salivary amylase gene, which increases production of this enzyme.Humans show a range of vulnerabilities to complex or infectious diseases, such as pulmonary tuberculosis. Despite an exhaustive search, no obvious, major resistance or susceptibility genes for tuberculosis have been found, although many genes—each with minor effects—have a role in disease susceptibility. Further support for the argument that resilience comes from diversity is found in the confusion around genetic association studies in many complex diseases, in which a given gene might be significantly associated with a condition in one population, but not in others. I suspect that many of these reports can be explained by the fact that susceptibility is caused by cumulative functional changes in many genes along different routes in different groups of humans or animals. In fact, susceptibility to a common disease conferred by a single, major locus would make the organism extremely vulnerable—which is exactly what we see with autosomal-dominant inherited diseases. Thus, it is unlikely that complex diseases are caused by a solitary gene defect, as evolution would select against the high risk of a single dominant effect. Instead, we see a range of conditions and phenotypes, owing to the large number of genes involved.This diversity of genetic factors is a blessing for humanity, as it has equipped us with enormous resilience against many common diseases, from cancer to coronary heart disease, to infectious diseases. But, it is also a bane for the geneticist and the clinical scientists who search for genetic factors that can be used to predict disease susceptibility, or the condition or progress of disease. Complexity and diversity make things far more unpredictable and messy—and therefore more difficult for scientific analysis—but both also ensure our survival against a daily assault of biotic and abiotic stressors.     

Motion control of musculoskeletal systems with redundancy

Motion control of musculoskeletal systems for functional electrical stimulation (FES) is a challenging problem due to the inherent complexity of the systems. These include being highly nonlinear, strongly coupled, time-varying, time-delayed, and redundant. The redundancy in particular makes it difficult to find an inverse model of the system for control purposes. We have developed a control system for multiple input multiple output (MIMO) redundant musculoskeletal systems with little prior information. The proposed method separates the steady-state properties from the dynamic properties. The dynamic control uses a steady-state inverse model and is implemented with both a PID controller for disturbance rejection and an artificial neural network (ANN) feedforward controller for fast trajectory tracking. A mechanism to control the sum of the muscle excitation levels is also included. To test the performance of the proposed control system, a two degree of freedom ankle–subtalar joint model with eight muscles was used. The simulation results show that separation of steady-state and dynamic control allow small output tracking errors for different reference trajectories such as pseudo-step, sinusoidal and filtered random signals. The proposed control method also demonstrated robustness against system parameter and controller parameter variations. A possible application of this control algorithm is FES control using multiple contact cuff electrodes where mathematical modeling is not feasible and the redundancy makes the control of dynamic movement difficult.     

Quantifying structural redundancy in ecological communities

In multivariate analyses of the effects of both natural and anthropogenic environmental variability on community composition, many species are interchangeable in the way that they characterise the samples, giving rise to the concept of structural redundancy in community composition. Here, we develop a method of quantifying the extent of this redundancy by extracting a series of subsets of species, the multivariate response pattern of each of which closely matches that for the whole community. Structural redundancy is then reflected in the number of such subsets, which we term “response units”, that can be extracted without replacement. We have applied this technique to the effects of the Amoco-Cadiz oil-spill on marine macrobenthos in the Bay of Morlaix, France, and to the natural interannual variability of macrobenthos at two stations off the coast of Northumberland, England. Structural redundancy is shown to be remarkably high, with the number and sizes of subsets being comparable in all three examples. Taxonomic/functional groupings of species within the differing response units change in abundance in the same way over time. The response units are shown to possess a wide taxonomic spread and, using two different types of randomisation test, demonstrated to have a taxonomically and functionally coherent structure. The level of structural redundancy may therefore be an indirect measure of the resilience or compensation potential within an assemblage. Received: 23 January 1996 / Accepted: 14 July 1997     

Interpreting genotype-by-environment interaction using redundancy analysis

Summary Methods for the interpretation of genotype-by-environment interaction in the presense of explicitly measured environmental variables can be divided into two groups. Firstly, methods that extract environmental characterizations from the data itself, which are subsequently related to measured environmental variables, e.g., regression on the mean or singular value decomposition of the matrix of residuals from additivity, followed by correlation, or regression, methods. Secondly, methods that incorporate measured environmental variables directly into the model, e.g., multiple regression of individual genotypical responses on environmental variables, or factorial regression in which a genotype-by-environment matrix is modelled in terms of concomitant variables for the environmental factor. In this paper a redundancy analysis is presented, which can be derived from the singular-value decomposition of the residuals from additivity by imposing the restriction on the environmental scores of having to be linear combinations of environmental variables. At the same time, redundancy analysis is derivable from factorial regression by rotation of the axes in the space spanned by the fitted values of the factorial regression, followed by a reduction of dimensionality through discarding the least explanatory axes. Redundancy analysis is a member of the second group of methods, and can be an important tool in the interpretation of genotype-by-environment interaction, especially with reference to concomitant environmental information. A theoretical treatise of the method is given, followed by a practical example in which the results of the method are compared to the results of the other methods mentioned.