sh-2超甜玉米乳熟期籽粒重量和碳水化合物变化及与温度降雨量的回归分析

采用夏季不同播期,研究了sh-2型超甜玉米乳熟期籽粒重量和碳水化合物的变化,用多重回归分析方法对气温、降雨量与籽粒重量、碳水化合物含量的关系进行了分析．结果表明,两个播期的可溶性总糖、果糖、蔗糖含量变化趋势有明显差异．夏季早播,提高了乳熟期籽粒鲜重和干重,灌浆速率,可溶性总糖和淀粉含量．说明夏季早播有利于提高甜玉米的独特甜风味和产量构成．移栽-收获期的T（温差）、K（有效积温）和RF（降雨量）是影响乳熟期籽粒鲜重和干重及可溶性总糖、果糖、蔗糖、淀粉含量的主要因子,K、RF表现正相关效应;在授粉-收获期,K是影响的主要因子,K与籽粒鲜重和干重及果糖、淀粉含量呈正相关,与籽粒蔗糖含量呈负相关．     

氯化胆碱浸种对烟草幼苗某些生理特性的影响

烟草种子经氯化胆碱(CC)溶液浸种后,萌发种子的呼吸速率和α-淀粉酶活性提高,烟苗茎高和根系伸长受抑制,但根系活力和单位长度内苗干重显著增加;幼苗叶片中可溶性糖、可溶性蛋白质和叶绿素含量提高;超氧化物歧化酶(SOD)、过氧化物酶(POD)和硝酸还原酶(NR)活性也随氯化胆碱浓度的增大而明显提高.     

文心兰原球茎形态发生与可溶性物质及抗氧化酶的关系

以文心兰切花品种'南茜'无菌苗为材料,取其茎尖通过组织培养诱导形成原球茎和幼苗,观察并分析了原球茎各形态发生阶段的特征及其可溶性糖和蛋白质含量、抗氧化酶(POD、CAT和SOD)活性以及相关同功酶(POD、EST和SOD)的变化.结果显示:(1)文心兰原球茎形态发生可分为外植体期、外植体膨大期、愈伤组织期、原球茎形成期、原球茎成熟期、叶鞘伸展期、顶端腋芽发育期及幼苗期8个阶段.(2)可溶性糖和蛋白质含量均在叶鞘伸展期出现最大峰值;POD活性在外植体膨大期、CAT和SOD活性在愈伤组织期分别出现最大峰值.SOD同工酶的2条酶带在愈伤组织期到幼苗期交替出现;EST同工酶在原球茎形成期有2条特异酶带.研究表明,可溶性糖和蛋白质的含量以及POD、CAT、SOD活性的特异变化与文心兰茎尖脱分化及原球茎再分化的实现密切相关,不同类型的同工酶在原球茎同一发生阶段表现出较大差异,EST同工酶的2条特异酶带可作为原球茎形成的标志.     

NaHS对NaHCO_3胁迫下黑籽南瓜种子萌发及生理特性的影响

以黑籽南瓜(Cucurbita ficifolia)种子为试材,研究了外施不同浓度的NaHS对NaHCO3胁迫下种子萌发及生理特性的影响。结果表明,NaHCO3胁迫显著抑制了黑籽南瓜种子的发芽率、胚轴长和胚根长,降低了种子萌发过程中的可溶性糖含量,抑制了α-淀粉酶、β-淀粉酶、SOD及POD活性。而外施不同浓度的NaHS显著促进了NaHCO3胁迫下黑籽南瓜萌发种子胚轴和胚根的生长,提高了可溶性糖含量及α-淀粉酶、β-淀粉酶、SOD和POD活性,降低了MDA含量;外施其它盐类(Na2S、Na2SO4、NaHSO4和NaHSO3)及不同pH值(pH5.8–7.8)的Na2HPO4-NaH2PO4缓冲液对NaHCO3胁迫下黑籽南瓜种子的萌发则无影响。外施NaHS可有效缓解NaHCO3胁迫对黑籽南瓜种子萌发的抑制作用,其缓解效应可能与其释放的H2S有关。     

低温胁迫对麻竹叶片和根系抗性生理指标的影响

采用室内人工低温处理,研究了麻竹(Dendrocalamus latiflorus)叶片及根部质膜透性、丙二醛、可溶性蛋白、可溶性糖含量,超氧化物歧化酶(SOD)、过氧化物酶(POD)活性和膜脂脂肪酸组成的变化,寻找与竹类植物耐寒性关系最密切的抗性生理指标。结果表明:低温预处理(8℃)15d后,麻竹叶片中可溶性糖、可溶性蛋白含量、POD活性显著提高,根部可溶性糖含量、POD活性显著升高;低温胁迫处理(-2℃)72h后,经低温预处理的麻竹叶片可溶性糖、可溶性蛋白质含量、SOD、POD活性显著高于未经低温预处理,而质膜透性显著低于未经低温预处理,但膜脂过氧化程度显著高于-2℃处理前;经低温预处理的麻竹根部SOD、POD活性及膜脂不饱和脂肪酸相对含量显著高于未经低温预处理,而质膜透性、膜脂过氧化程度较-2℃处理前无显著差异。说明剧烈降温对麻竹生理特征造成严重影响,叶片通过提高可溶性蛋白、可溶性糖含量,维持较高的POD活性以减轻低温伤害;根系则通过维持较高的SOD、POD活性以减轻低温下膜脂过氧化水平,并通过提高膜脂不饱和脂肪酸比例降低质膜透性来抵御低温对膜的伤害。     

水淹对铺地黍部分生理指标的影响

研究了水淹对铺地黍幼苗的丙二醛、可溶性糖和可溶性蛋白质含量,3种抗氧化保护酶(SOD、CAT和POD)活性等生理指标的影响.结果显示:水淹胁迫下,铺地黍幼苗的丙二醛含量缓慢升高,可溶性糖含量先升高后下降,蛋白质含量逐渐下降,超氧化物歧化酶(SOD)和过氧化氢酶(CAT)活性先上升后下降,而过氧化物酶(POD)活性则持续...     

外源NO对酸雨胁迫下龙眼幼苗生理特性的影响

研究了外源NO供体硝普钠(SNP)对pH3.0酸雨胁迫下龙眼幼苗叶绿素含量、抗氧化酶活性和渗透调节物质含量的影响.结果表明:酸雨胁迫下,龙眼幼苗叶片中的超氧化物歧化酶(SOD)、过氧化物酶(POD)和过氧化氢酶(CAT)活性降低,叶绿素、蛋白质和可溶性糖含量下降,丙二醛含量升高,呈现出一定的毒害效应.外源NO对酸雨胁迫下龙眼幼苗的生理代谢的作用具有双重性,0.1 ～0.5.mmol·L-1SNP显著提高叶绿素、可溶性糖和蛋白质含量,增强SOD、POD和CAT活性,降低丙二醛含量;其中0.5 mmol·L-1 SNP处理效果最好,叶绿素、可溶性糖和蛋白质含量分别比单独酸雨胁迫处理增加了76.0％、107.0％和216.1％,SOD、POD和CAT活性分别提高150.0％、350.9％和97.1％,丙二醛含量降低了46.4％.低浓度外源NO能通过刺激抗氧化酶活性来清除活性氧,减轻氧化胁迫,缓解酸雨胁迫对龙眼幼苗的毒害作用;而高浓度外源NO对酸雨胁迫的缓解作用减弱.     

氯化胆碱对盐胁迫黄瓜幼苗渗透调节物质及活性氧代谢系统的影响

以盐敏感型黄瓜品种津春4号为材料,采用水培方法研究了叶面喷施不同浓度(0.5、1.0和1.5 mmol·L-1)氯化胆碱(CC)对NaCl胁迫(75 mmol·L-1)下黄瓜幼苗鲜重、叶片叶绿素、渗透调节物质含量及活性氧代谢系统的影响.结果表明:(1)单独CC处理可提高黄瓜叶片的叶绿素、可溶性糖和可溶性蛋白含量以及过氧化氢酶(CAT)与过氧化物酶(POD)活性,降低O2·-产生速率,但对植株鲜重及超氧化物岐化酶(SOD)活性影响不大;(2)NaCl胁迫处理增加了黄瓜幼苗叶片中可溶性糖和可溶性蛋白含量,增强了SOD、POD和CAT活性,提高了O2·-产生速率及丙二醛(MDA)的含量,但同时降低了叶绿素含量与植株鲜重;(3)盐胁迫前CC预处理可缓解黄瓜幼苗叶绿素含量和植株鲜重的下降、以及MDA含量和O2·-产生速率的上升趋势,且进一步提高了盐胁迫下黄瓜叶片中SOD、POD和CAT活性.因此,适宜浓度的氯化胆碱可显著提高盐胁迫下黄瓜叶片的抗氧化酶活性,提高清除活性氧的能力,缓解盐胁迫对黄瓜幼苗细胞膜的伤害,增强黄瓜幼苗的耐盐性.     

逆境条件下小麦种子活力与种子萌发相关酶活性及其基因表达的关系

分析不同基因型小麦品种逆境萌发过程中种子萌发相关酶活性及基因表达差异,明确在逆境条件下,种子活力与种子萌发相关酶活性及基因表达量的关系.通过标准发芽试验和逆境(冷浸、人工老化、干旱胁迫)发芽试验,测定4个小麦品种种子活力、萌发过程中可溶性总糖和可溶性蛋白含量、α-淀粉酶活性、半胱氨酸蛋白酶活性及相关基因表达量.结果表明:干旱、人工老化和冷浸胁迫3种逆境对种子活力都有一定影响.不同萌发条件下,可溶性总糖含量呈现先小幅度升高后小幅度降低再迅速升高的趋势;而可溶性蛋白含量随着萌发时间的延长呈现逐渐下降的趋势.α-淀粉酶活性整体呈现逐渐升高的趋势,但在冷浸胁迫处理后,豫农949和轮选061的α-淀粉酶活性在萌发60 h后出现下降.半胱氨酸蛋白酶活性整体呈先降低后升高的趋势,但在干旱胁迫条件下,豫农949、豫麦49-198和轮选061的半胱氨酸蛋白酶活性呈现先升高后降低再升高的趋势.不同逆境萌发条件下,α-AMY(α-淀粉酶基因)表达量整体呈先上升后下降的趋势.冷浸胁迫处理后,轮选061的α-AMY表达量高于对照,在其他逆境萌发条件下,4个品种的α-AMY表达量均低于对照;人工老化处理后,长4738的CP(半胱氨酸蛋白酶基因)表达量与对照差异不显著,在其他逆境萌发条件下,4个品种的CP表达量均高于对照.种子萌发期间,不同萌发条件下α-淀粉酶和半胱氨酸蛋白酶活性与其基因表达并没有直接关系,α-淀粉酶活性与可溶性总糖含量达到显著正相关,半胱氨酸蛋白酶活性与可溶性蛋白含量的相关性不显著.在标准发芽条件下,α-淀粉酶活性与活力指数呈显著正相关,而在逆境萌发过程中,其相关性不显著.冷浸胁迫处理后,半胱氨酸蛋白酶活性与活力指数呈显著正相关,但在标准发芽、干旱胁迫、人工老化处理后,其相关性不显著.     

孕穗期低温对冬小麦生理生化特性和产量的影响

为明确孕穗期低温对小麦生理生化特性和产量的影响,以‘小偃22’等5个冬小麦品种为材料,对其在低温（2±1） ℃胁迫下叶片中超氧化物歧化酶(SOD)活性、过氧化物酶(POD)活性、过氧化氢酶(CAT)活性、丙二醛(MDA)含量、相对电导率、可溶性糖含量、脯氨酸含量和可溶性蛋白含量等生理指标进行测定,并测定单株产量。结果表明:（1）与对照相比,低温胁迫24 h和48 h后,供试品种叶片SOD活性、POD活性、CAT活性、MDA含量、相对电导率、可溶性糖含量和脯氨酸含量均显著增加,而可溶性蛋白含量显著降低。（2）低温胁迫使各品种单株籽粒产量和单株穗粒数显著下降,但对小穗数和千粒重的影响不大。（3）经隶属函数分析,‘小偃22’、‘矮抗58’和‘西农509’属于抗寒性较强的品种,而‘郑麦9023’和‘郑麦366’为抗寒性较弱的品种,这与它们在试验中的籽粒产量表现相符。研究发现,与抗寒性弱的小麦品种相比,抗寒性强的品种在相同低温下具有相对较高的保护酶活性、较强的渗透调节物质积累能力和较低的质膜破坏程度,这是其在低温胁迫后能维持较高产量的生理基础。     

A Study on the Triglyceride Composition in Apricot Kernel Oil,Peach Kernel Oil and Plum Kernel Oil

The triglyceride composition of kernel oils from apricot, peach and plum was separated and analysed by reverse phase high performance liquid chromatography (RP-HPLC). The results showed that their oils predominantly contained OOO and OLO among 11 triglycerides.     

Kernel stick-breaking processes

We propose a class of kernel stick-breaking processes for uncountable collections of dependent random probability measures. The process is constructed by first introducing an infinite sequence of random locations. Independent random probability measures and beta-distributed random weights are assigned to each location. Predictor-dependent random probability measures are then constructed by mixing over the locations, with stick-breaking probabilities expressed as a kernel multiplied by the beta weights. Some theoretical properties of the process are described, including a covariate-dependent prediction rule. A retrospective Markov chain Monte Carlo algorithm is developed for posterior computation, and the methods are illustrated using a simulated example and an epidemiological application.     

Genetic Dissection of Wheat Kernel Hardness Using Conditional QTL Mapping of Kernel Size and Protein-Related Traits

Kernel hardness (KH) is one of the primary quality parameters for common wheat (Triticum aestivum L.) and has a major impact on milling, flour quality, and end-product properties. In addition to Puroindoline (Pin) mutations and differences in Pin expression, other factors, such as kernel size and protein-related traits, play noticeable roles in determining hardness, but at the quantitative trait locus (QTL) level, the influence of these factors remains unclear. In this study, genetic relationships between KH and kernel size traits and between KH and protein-related traits were demonstrated by unconditional and conditional mapping using a wheat 90K genotyping assay with a segregating population of 173 recombinant inbred lines in four environments. Eight additive QTL for KH were detected using unconditional QTL mapping analysis; these QTL were primarily distributed on chromosomes 4B, 5A, 5B, and 6D, with phenotypic variation that ranged from 0.2 to 17.7%. In addition, one pair of epistatic QTL (QKH3B.4-65/QKH4B.6-2) was identified by unconditional mapping, and this pair accounted for 1.6% of the phenotypic variation. Through conditional mapping, after excluding the influences of kernel size and protein-related traits, 14 QTL were discovered and accounted for 0.6–18.5% of the phenotypic variation. Of them, the stable QTL QKH4B.4-17 made the largest contribution, which was partially contributed by the kernel length (KL), kernel thickness (KT), and dry gluten content (DGC). Furthermore, QKH4B.4-17 was crucially contributed by the kernel width (KW), kernel diameter (KD), kernel protein content (KPC), and wet gluten content (WGC) and was independent of the sedimentation volume (SV) and gluten index (GI). Another major QTL, QKH5B.10-63, was independent of the KW and KT; partly due to the variations in KL, KD, DGC, and WGC; and conclusively contributed by the KPC, SV, and GI. Seven additional QTL were only detected in the conditional analysis and were crucially contributed by kernel size or protein-related traits. These results demonstrated that kernel size and protein-related traits play significant roles in determining KH. The present study increases the understanding of the relationships between KH and kernel size and between KH and protein-related traits at the QTL level.     

Flexible Kernel Memory

This paper introduces a new model of associative memory, capable of both binary and continuous-valued inputs. Based on kernel theory, the memory model is on one hand a generalization of Radial Basis Function networks and, on the other, is in feature space, analogous to a Hopfield network. Attractors can be added, deleted, and updated on-line simply, without harming existing memories, and the number of attractors is independent of input dimension. Input vectors do not have to adhere to a fixed or bounded dimensionality; they can increase and decrease it without relearning previous memories. A memory consolidation process enables the network to generalize concepts and form clusters of input data, which outperforms many unsupervised clustering techniques; this process is demonstrated on handwritten digits from MNIST. Another process, reminiscent of memory reconsolidation is introduced, in which existing memories are refreshed and tuned with new inputs; this process is demonstrated on series of morphed faces.     

Kernel and nonlinear canonical correlation analysis

We review a neural implementation of the statistical technique of Canonical Correlation Analysis (CCA) and extend it to nonlinear CCA. We then derive the method of kernel-based CCA and compare these two methods on real and artificial data sets before using both on the Blind Separation of Sources.     

Kernel Abortion in Maize : II. Distribution of C among Kernel Carbohydrates

This study was designed to compare the uptake and distribution of ¹⁴C among fructose, glucose, sucrose, and starch in the cob, pedicel, and endosperm tissues of maize (Zea mays L.) kernels induced to abort by high temperature with those that develop normally. Kernels cultured in vitro at 30 and 35°C were transferred to [¹⁴C]sucrose media 10 days after pollination. Kernels cultured at 35°C aborted prior to the onset of linear dry matter accumulation. Significant uptake into the cob, pedicel, and endosperm of radioactivity associated with the soluble and starch fractions of the tissues was detected after 24 hours in culture on labeled media. After 8 days in culture on [¹⁴C]sucrose media, 48 and 40% of the radioactivity associated with the cob carbohydrates was found in the reducing sugars at 30 and 35°C, respectively. This indicates that some of the sucrose taken up by the cob tissue was cleaved to fructose and glucose in the cob. Of the total carbohydrates, a higher percentage of label was associated with sucrose and a lower percentage with fructose and glucose in pedicel tissue of kernels cultured at 35°C compared to kernels cultured at 30°C. These results indicate that sucrose was not cleaved to fructose and glucose as rapidly during the unloading process in the pedicel of kernels induced to abort by high temperature. Kernels cultured at 35°C had a much lower proportion of label associated with endosperm starch (29%) than did kernels cultured at 30°C (89%). Kernels cultured at 35°C had a correspondingly higher proportion of ¹⁴C in endosperm fructose, glucose, and sucrose. These results indicate that starch synthesis in the endosperm is strongly inhibited in kernels induced to abort by high temperature even though there is an adequate supply of sugar.     

Kernel estimates of dose response

A nonparametric method for analyzing quantal response data from an indirect bioassay experiment is proposed. Kernel estimates of the dose-response curve are used to develop approximate confidence intervals for (i) the optimal combination dose of a drug with therapeutic effects at low doses and toxic effects at high doses, and (ii) the lethal dose levels of a toxic chemical. This nonparametric procedure was implemented on real and simulated data. The confidence interval for problem (i) has high coverage probabilities when the dose-response curve is symmetric about the optima. However, the coverage probabilities are adversely affected by asymmetry about the optima and consequently are not reliable unless the sample sizes are large. The use of kernel estimators with higher-order kernels may alleviate this sensitivity to asymmetry. The confidence interval for problem (ii) has high coverage probabilities robust with respect to the shape or symmetry of the underlying dose-response curve.     

The Kernel of Maximum Agreement Subtrees

A Maximum Agreement SubTree (MAST) is a largest subtree common to a set of trees and serves as a summary of common substructure in the trees. A single MAST can be misleading, however, since there can be an exponential number of MASTs, and two MASTs for the same tree set do not even necessarily share any leaves. In this paper, we introduce the notion of the Kernel Agreement SubTree (KAST), which is the summary of the common substructure in all MASTs, and show that it can be calculated in polynomial time (for trees with bounded degree). Suppose the input trees represent competing hypotheses for a particular phylogeny. We explore the utility of the KAST as a method to discern the common structure of confidence, and as a measure of how confident we are in a given tree set. We also show the trend of the KAST, as compared to other consensus methods, on the set of all trees visited during a Bayesian analysis of flatworm genomes.