Yield stability and relationships among stability parameters in faba bean(Vicia faba L.) genotypes

Sixteen faba bean genotypes were evaluated in 13 environments in Ethiopia during the main cropping season for three years(2009–2011). The objectives of the study were to evaluate the yield stability of the genotypes and the relative importance of different stability parameters for improving selection in faba bean. The study was conducted using a randomized complete block design with four replications. G × E interaction and yield stability were estimated using 17 different stability parameters. Pooled analysis of variance for grain yield showed that the main effects of both genotypes and environments, and the interaction effect, were highly significant(P ≤ 0.001) and(P ≤ 0.01), respectively. The environment main effect accounted for 89.27% of the total yield variation, whereas genotype and G × E interaction effects accounted for 2.12% and 3.31%, respectively.Genotypic superiority index(Pi) and FT3 were found to be very informative for selecting both high-yielding and stable faba bean genotypes. Twelve of the 17 stability parameters,including CVi, RS, α, λ, S2 di, bi, S(2)i, Wi, σ2i, EV, P59, and ASV, were influenced simultaneously by both yield and stability. They should accordingly be used as complementary criteria to select genotypes with high yield and stability. Although none of the varieties showed consistently superior performance across all environments, the genotype EK 01024-1-2ranked in the top third of the test entries in 61.5% of the test environments and was identified as the most stable genotype, with type I stability. EK 01024-1-2 also showed a17.0% seed size advantage over the standard varieties and was released as a new variety in2013 for wide production and named "Gora". Different stability parameters explained genotypic performance differently, irrespective of yield performance. It was accordingly concluded that assessment of G × E interaction and yield stability should not be based on a single or a few stability parameters but rather on a combination of stability parameters.

Genotype by Environment Interaction for Grain Yield and Association among Stability Parameters in Bread Wheat (<i>Triticum aestivum</i>L.)

Bread wheat (Triticum aestivum L.) is most important cereal crop in Ethiopia. Lack of genotypes with wide stability across environments has been one of the most important constraints of wheat production in the country. Field experiments were conducted in Halaba and Bule, South Ethiopia, in 2016 and 2017, in order to estimate grain yield stability and association among stability parameters. Fifteen improved bread wheat genotypes were grown under randomized complete block design with three replications. Mean yield for Halaba 2016, Halaba 2017, Bule 2016 and Bule 2017 was 3.83, 1.89, 2.90 and 3.59 tons/ha, respectively. Genotypes Lemu (3.25 tons/ha) and Mandoyu (3.18 tons/ha) had high mean yield, and low values of environmental variance (S2i), coefficient of variation (CVi), stability variance (δ2i), ecovalence (Wi) and deviation from regression (S2di). Genotypes Biqa (3.69 tons/ha) and Shorima (3.66 tons/ha) had high mean yield, coefficient of regression (bi) and coefficient of determination (R2i ≥ 0.94) as well as low values of δ2i, Wi and S2di. Grain yield had positive rank correlation with bi (r = 0.75, p 2i (r = 0.70, p δ2i, Wi and S2di was high (r ≥ 0.98, p , Mandoyu and Hidase, and Biqa and Shorima would be recommended for wide adaption, and for more favorable environments, respectively. It could also be suggested that one of Wi, δ2i, S2di and rank sum would be used for ranking of genotypes.

Additive Main Effects and Multiplicative Interaction and Other Stability Analyses of Tef [<i>Eragrostis tef</i>(Zucc.)Trotter] Grain Yield

Tef [Eragrostis tef (Zucc.)Trotter]) is one of the most important cereal crops grown in Ethiopia. Tef production has been partly constrained by low yield and less stability of the genotypes under cultivation. Field experiments were carried out in Halaba, Loka Abaya, Bensa and Areka, South Ethiopia, from August to November, during 2016 and 2017 main cropping seasons, in order to estimate yield stability and the association between AMMI analysis and other stability parameters. Experiments were laid out in randomized complete block design with three replications using fourteen improved tef genotypes. Mean yield for Halaba, Loka Abaya2016, Loka Abaya2017, Bensa, Areka2016 and Areka2017 was 0.99, 0.45, 0.48, 1.50, 1.62 and 0.77 tons/ha, respectively. Genotypes Amarach, Boset, Simada, and Tseday exhibited high mean yield of 1.09, 1.10, 1.07 and 1.07 tons/ha, respectively. AMMI stability value (ASV) ranged from 0.17 (genotype Lakech) to 1.40 (Amarach);yield stability index (YSI) from 7 (Lakech) to 25 (Quncho);and superiority measure (Pi) from 0.015 (Boset) to 0.145 (Dega Tef). Rank correlation of yield with Pi (r = 0.97, p < 0.01), ASV with Wi and δi2 (r = 0.85, p < 0.01) and that between Wi and δi2 (r = 1.00, p < 0.01) was high. Rank correlation of YSI with yield (r = 0.57, p < 0.05), ASV (r = 0.75, p < 0.01), and Pi (r = 0.68, p < 0.01) and Wi and δi2 (r = 0.67, p < 0.01) was also positive. The present study showed that genotypes Etsub, Simada and Tseday would be recommended for high yield and wide adaptation, and ASV would be used alone or jointly with YSI, Wi and δi2 for ranking of genotypes.

Parameter Sensitivity and Qualitative Analysis of Dynamics of Ovarian Tumor Growth Model with Treatment Strategy

In this paper, we are interested to find the most sensitive parameter, local and global stability of ovarian tumor growth model. For sensitivity analysis, we use Latin Hypercube Sampling (LHS) method to generate sample points and Partial Rank Correlation Coefficient (PRCC) method, uses those sample points to find out which parameters are important for the model. Based on our findings, we suggest some treatment strategies. We investigate the sensitivity of the parameters for tumor volume, y, cell nutrient density, Q and maximum tumor size, ymax. We also use Scatter Plot method using LHS samples to show the consistency of the results obtained by using PRCC. Moreover, we discuss the qualitative analysis of ovarian tumor growth model investigating the local and global stability.

保大麦25号高产稳产性及产量构成因素分析

为了使保大麦25号在生产中发挥更大的增产潜能,以2016—2017年保山市大麦多点试验以及2017—2019年云南省饲料大麦区域试验数据为分析资料,对保大麦25号的丰产性、稳定性、适应性及其产量构成因素进行多重分析,结果表明保大麦25号的丰产性、稳定性、适应性均优于对照品种。主要农艺性状中与产量相关程度由高到低依次为穗实粒数(0.3973)、有效穗(0.3560)、茎蘖总数(0.2052)、株高(0.1550)、千粒重(0.0707)、基本苗(0.0003);对产量的直接影响由高到低依次是穗实粒数(0.4987)、千粒重(0.4249)、有效穗(0.3605)、株高(0.2683)、茎蘖总数(0.2335)、基本苗(0.0652);与产量的关联度由高到低依次是穗实粒数(0.4611)、株高(0.4583)、有效穗(0.4377)、千粒重(0.4180)、茎蘖总数(0.3866)、基本苗(0.3642)。

微波预处理对花生压榨特性的影响

采用微波对花生进行预处理,研究处理前后花生水分、褐变程度、颗粒质构参量、水分状态分布、蛋白变性程度的变化趋势以及对压榨出油率的影响,并与真空烘箱处理作对比,经Pearson相关性分析,建立各指标与出油率之间的数学相关性,为花生的高效加工利用提供理论依据和数据参考。结果表明,花生在900 W条件下微波7 min,或者85℃真空烘箱烘制89 min,水分质量分数从5.25%降至2.27%,此时压榨出油率最高,分别为45.85%和45.76%;此条件下,花生与榨油机之间构成的切应力适中,花生受到充分挤压,发生形变,油脂大量流出,且花生可塑性最好,水分状态组成最为合理,蛋白变性程度适中,既可以使得油脂大量流出,又不会轻易破碎影响饼粕成形。

辽宁省水稻品种品质性状及丰稳性分析

以2023年辽宁省水稻区域试验中晚熟组的23个品种试验数据为基础进行品种品质性状和丰产性、稳定性分析。结果表明:11个品质性状的变异系数在0.93%~70.00%,11个品质性状间存在着不同程度的相关性,加工因子、直链淀粉因子、碱消因子、垩白因子、蛋白质因子共同影响着品种品质性状的综合表现。利用变异系数、回归系数、高稳系数、品种产量对23个品种进行丰稳性分析,结果表明:高稳系数、回归系数、品种产量可较好的区分品种的丰产性、稳产性,同时,水稻品种丰产性与稳定性参数间存在着明显的负相关性。在此基础上,通过聚类分析、方差比较显示出天隆粳224、辽粳169、盐粳66、天隆粳234、天隆粳788、花粳1607、盐粳945、辽粳1920等品种产量水平和稳定性较好。

杂交水稻产量性状稳定性及其相关性研究

在 AMMI模型分析杂交水稻组合的产量及产量构成因素稳定性的基础上 ,进一步分析了性状稳定性之间及其与性状值之间的关系 ,结果表明 ,各性状的基因型和试点效应均达 1%显著水平 ;除有效穗外 ,其余性状还存在基因型与试点的互作效应 ,且以千粒重表现最稳定。产量稳定性与结实率稳定性间、每穗粒数的稳定性分别与千粒重和结实率的稳定性间均呈显著正相关 ;每穗粒数的稳定性值与千粒重之间、结实率稳定性值与结实率之间均呈显著负相关。

品种稳定性参数和高稳系数在小麦区试中的应用及其分析

经过试验 ,用高稳系数法分析品种的高产稳定性 ,计算简便且分析容易 ,但比较粗放。回归系数座标分析法较为详细准确 ,缺点是比较繁琐。所以在对区试结果不需详细分析时 ,用高稳系数法较简便容易 ;如需详细分析时 ,则用回归系数座标分析法较准确可靠。同时对几种品种稳定性参数的准确性进行了比较分析 ,结果表明品种间回归系数的大小能较准确地反映出品种间稳定性差异程度的大小 。

LHS方法在边坡可靠度分析中的应用

Monte Carlo(MC)法在目前边坡可靠度分析中是一种相对精确的方法,应用广泛,受问题限制的影响较小,适应性很强,其误差仅与标准差和样本容量有关。但其精度受随机抽样的可靠性和模拟次数制约,收敛速度慢,影响了实际使用。在极限平衡方法的基础上,用拉丁超立方抽样(Latin hypercube sampling,LHS)方法代替MC法的随机抽样,考虑边坡参数的变异性和相关性进行边坡可靠度分析。讨论了LHS法、MC法中可靠指标的各种计算方法,建议以破坏概率、安全系数均值和标准差作为评价指标。算例显示LHS法较MC法效率上有很大改善:较少的抽样样本就能反映参数的概率分布,可靠度分析收敛快,不需要大量的模拟,因此,值得在边坡可靠度分析中推广应用。也将工程上常用的均匀设计和正交设计用于边坡可靠度分析,结果表明,正交设计结果和中心点法比较接近,而均匀设计得到的结果则是不可靠的。

材料的双轴拉伸的规律的研究

汽车车身覆盖件是冲压成型的,其覆盖件的高精度回弹量计算非常困难,并少见有研究和报道。由于冲压成型过程是一个大应变和塑性屈服,常规的拉伸试验机无法测出其应力应变曲线,而目前汽车工业领域还没有建立用于修正回弹量的数据库,所以必须通过数值模拟和实验的方法对汽车车身覆盖件进行弹性模量、屈服强度和硬化规律进行研究。本实验研究的目的是通过对规定材料的双轴拉伸试验,应用数字图像处理的光测方法,确定材料屈服强化阶段复杂本构模型的材料特性常数,以达到正确合理描述复杂材料的硬化行为。试验中采用机械式拉伸试验机实现材料的双轴拉伸行为,利用数字相关光测方法获得拉伸材料屈服面屈服过程中大应变全场的数据,通过数字图像相关处理,得到材料在屈服强化阶段复杂本构模型的特性参数。实验研究的设备和仪器包括(1)双轴拉伸试验机;(2)计算机,高分辨率CCD和摄像头,图像卡,图像处理软件;(3)其它辅助设备等。实验研究设备的规范标准根据国家现行实验规范标准对本实验研究设备进行标定和计量审核。

测井资料与岩石力学参数相关性及其在井壁力学稳定性计算中的应用

应用大庆头台和茂兴地区５口井的测井资料，１４块岩心的室内试验数据，找出了该区块不同岩性在相应围压下的静、动态岩石弹性参数的相关性，根据线弹性理论以及岩石的破坏准则建立了井壁稳定性条件，确定了井壁破裂和坍塌的３个临界压力剖面，结合孔隙压力确定了头台和茂兴地区的安全钻井液密度剖面。

2014-2015年度长江中游组区试油菜稳定性探析

通过分析国家油菜品种区域试验长江中游组(2014-2015年度4组区试,每组包含对照在内共12个参试品种)的数据,探讨农艺性状稳定性对油菜丰产性和稳产性的影响。利用AMMI(加性主效应与复合交互效应)模型计算产量及农艺性状的敏感度来衡量各性状的稳定程度。在每个试验组内,根据品种的丰产性、稳产性和总体农艺性状稳定性对品种进行归类。通过回归分析和灰色关联分析,探讨农艺性状与产量两者敏感度之间的密切程度。利用Pearson相关分析,探讨农艺性状与产量性状两者敏感度之间的线性关系,及农艺性状敏感度之间的线性关系。结果表明,高、中产类型品种的产量和农艺性状敏感度中等或较低;低产类型品种农艺性状敏感度中等或较高,产量敏感度没有明显倾向。农艺性状与产量两者的敏感度之间存在显著的线性回归关系,农艺性状敏感度的联合线性作用能解释约70%的产量敏感度变异原因。一次分枝高度和一次分枝相对高度(一次分枝高度与株高的比值)、一次分枝数与单株角果数的敏感度之间有极显著的线性相关关系。千粒重、一次分枝数、主花序角果密度、分枝相对高度、每角粒数、生育期和菌核病病指敏感度与产量稳定性有较为密切关系。

龙开口水电站右岸大型变形岩体稳定性分析

龙开口水电站是金沙江中游河段的一座大型水电枢纽工程,其右岸发育一体积约1 000 m3的大型变形岩体,直接影响到工程的施工期及永久运行的安全。基于FLAC程序,采用强度折减法对该变形体的典型剖面III–III,在天然工况和8度地震工况条件下,分别进行应力–应变分析,确定该变形体的变形模式、塑性屈服区以及相应的稳定系数。研究结果对于保障龙开口大型水电枢纽工程的施工和安全运行具有重要的理论意义和实用价值。

保大麦20号高产稳产性及产量构成因素分析

为更全面详细地了解保大麦20号的生产特性,以2014—2015年保山市大麦多点试验以及2015—2017年云南省饲料大麦区域试验结果为资料,通过产量、变异系数、产量构成因素分别对保大麦20号的丰产性、稳定性、适应性及其产量构成因素进行相关和通径分析。结果表明,保大麦20号无论是丰产性、稳定性,还是适应性均优于对照品种,属高产稳产大麦新品种。主要农艺性状与产量相关程度由高到低依次为有效穗(0.641 3)、穗实粒数(0.530 0)、千粒重(-0.018 2)、基本苗(-0.137 1)、株高(-0.462 0);主要农艺性状对产量的直接影响由高到低依次为有效穗(0.473 3)、穗实粒数(0.326 2)、千粒重(0.025 0)、基本苗(-0.086 3)、株高(-0.304 8)。最后,提出了保大麦20号高产高效栽培技术:应保证正常数量基本苗,早施、重施种及分蘖肥,促进分蘖提高有效穗,及时灌分蘖水、抽穗杨花水提高结实率和千粒重。

花生主要光合性状对产量形成的重要性差异分析

为了明确不同光合性状在花生产量形成过程中的重要性差异,选择苗期、花针期、结荚期、饱果期和成熟期气孔导度、羧化效率、最大光化学效率、实际光化学效率、单株绿叶面积等主要光合性状与产量进行了灰色关联度分析。结果表明,在苗期、花针期和结荚期,羧化效率与花生产量的关联度最大,光合暗反应限制着光合产量的形成;而在饱果期和成熟期,气孔导度与花生产量的关联度最大,气孔张开的程度限制着花生产量的形成。

斑茅蔗BC_1后代产量性状遗传分析

对100份斑茅蔗BC1后代品系的有关产量性状进行遗传分析的结果表明,蔗茎产量、株高和茎径遗传力较高,小区有效茎数遗传力中等,单茎重的遗传力相对较低;蔗茎产量、小区有效茎数和单茎重的遗传变异系数较大,遗传进度也相应较大,株高和茎径的遗传变异程度和遗传进度都较小。遗传相关分析结果表明,产量与单茎重、株高相关关系密切,但后者的相关遗传进度较大。

玉米新品种在秦巴高海拔山区的适应性分析

用产量增产百分数、差异显著性、变异系数法、回归系数法、高稳系数法和非参数度量法等多种分析方法 ,对 10个玉米新品种在高海拔山区 4个地点的适应性进行了系统聚类。结果表明 ,农大 10 8、农大 3138、陕资1号、成单 18号、97Q- 16 7和中单 32 1等 6个品种在高海拔山区表现出较高的生产潜力和较强的稳定性 。

小麦品系籽粒蛋白产量与其它性状间的遗传参数及相关性研究

选用10个春小麦新品系,对单株籽粒蛋白产量与其它性状间的遗传变异系数、广义遗传力、遗传相关系数、广义相关遗传力等遗传参数进行了估算和分析。结果表明:影响蛋白产量的主要遗传因素是生物学产量、单株粒数和蛋白含量。利用它们对蛋白质产量性状进行间接选择的效率大于直接选择,但蛋白质含量为主要限制因素,选择时不宜要求过严。

岩屑试验参数与井眼稳定性的灰色关联研究

灰色系统理论中的灰关联系数法是评估各组研究数据之间相互关联和影响程度的有效方法,灰关联系数的大小能够直接反映所研究对象之间的关联程度,从而很容易看出众多对象与同一个研究对象之间关系的密切程度。文章用该方法优选岩屑试验参数,即从众多的岩屑试验参数中优选出对井眼稳定性影响较大的参数,参数的优选能够为钻井泥浆的配制提供直接依据,同时也为指导生产节约了时间。通过在油气田的应用证明,该方法克服了统计相关法的缺点,优选岩屑试验参数对地层岩性变化的适应能力强,并具有快速、有效,并与现场工程实践相符的优点。