不同施肥处理对南天竹幼苗生长及生理特性的影响

[目的]研究不同施肥量对南天竹苗木生长及生理的影响.[方法]试验在田间条件下,设置了不施肥对照(CK)、常规施肥(T50)、增量施肥(T100)3种施肥处理,测定南天竹的重要生长和生理指标.[结果]不同施肥处理下南天竹苗高、生物量、硝态氮、硝酸还原酶均呈T50>T100>CK的趋势.[结论]通过综合评价,适宜的施肥量为...     

不同强度静电场长期处理对3种作物几种光合生理指标的影响

在0.1、0.3和0.5 kV·cm-1不同场强的静电场长期作用下,大豆、黄瓜和油青菜心叶片的叶绿素含量、PSⅡ的潜在活性和原初光能转换效率、叶绿体Mg2 -ATP酶和Ca2 -ATP酶活性以及光合代谢产物可溶性蛋白和可溶性糖含量均有不同程度的提高,表明用静电场长期处理作物能够有效地改善作物的光合性能,促进作物的光合作用与光合产物的积累.不同作物对不同场强静电场的响应有所差异,本试验条件下,对大豆、黄瓜和油青菜心处理效果最好的静电场强度分别为0.1、0.3 和0.5 kV·cm-1.     

羧甲基纤维素钠对壤砂土水分运动及水力参数的影响

科学使用羧甲基纤维素钠(CMC)实现保水控盐对于滨海壤砂盐碱土改良具有重要意义,而明晰CMC对滨海壤砂土水分运动规律的影响是科学使用CMC的重要基础。为研究施加CMC滨海壤砂土水分运动规律,本文通过开展一维垂直土柱积水入渗试验,探索不同CMC施量(0、0.1、0.2、0.4、0.6 g?kg-1) 对壤砂土入渗特性、水分分布和土壤水力参数的影响。结果表明,施用CMC土壤的最终累积入渗量增加了4.90％～15.17％、达到预设湿润锋深度的入渗时间增加了61.90%～604.73%;Philip入渗模型参数吸渗率S和Green-Ampt模型参数KsSf均随CMC施量的增加而减少,吸渗率S和平均土壤水扩散率与CMC施量之间的数学关系分别可用二次多项式和指数函数来表示;CMC增强了土壤的持水能力,土壤剖面含水量提高了0.72%～3.74%;CMC通过改变土壤结构影响了土壤水力参数,滞留含水率θr、饱和含水率θs及进气吸力倒数α均与CMC施量呈正相关关系,而与饱和导水率Ks和形状系数n呈反比关系。通过对变异系数CV的分析发现,CMC对饱和导水率Ks和进气吸力倒数α影响表现为中等差异,对滞留含水率θr、饱和含水率θs和形状系数n表现为弱差异。研究结果揭示了CMC对滨海壤砂土减渗保水的内在机理,为滨海盐碱地的改良提供了理论参考。     

关中平原农田土壤水力参数空间分异与模拟

土壤水力参数是土壤水分和污染物迁移等陆面过程数值模拟的重要基础参数。为探明关中平原农田土壤水力参数空间分异特征,建立空间分布预测模型,在关中平原网格布设124个样点,采集根层0-20 cm原状和扰动土壤样品,利用van Genuchten模型拟合获取土壤水分特征曲线,获得残余含水量(θr)、饱和含水量(θs)以及系数α和n等土壤水力参数。采用经典统计学、地统计学和结构方程方法分析了θr、θs、α和n的空间变异特征及影响因子,建立了水力参数传递函数预测模型。结果表明:θr和α为强变异,θs为中等变异,n为弱变异。θr、θs、α和n半方差函数最佳拟合模型分别为球状模型、指数模型、指数模型和球状模型。θs和n具有强烈的空间依赖性,变程分别为32.7,54.3 km;θr和α具有中等程度空间依赖性,变程均为52.8 km。土壤质地、容重、pH、有机质和海拔是影响土壤水力参数空间分布的主要因子。基于土壤理化性质和海拔建立的水力参数传递函数模型具有较好的模拟效果,可用于关中地区大尺度农田生态系统土壤水力参数的模拟预测。     

Detachment of road surface soil by flowing water

An agricultural watershed generally consists of two land use categories, farmland and the unpaved road or path networks with different traffic frequency and size. Road surfaces are quite different from farmland soil in physical properties, resulting in it's distinguish production transportation process. Hydraulic flume experiments were conducted with the flow discharges ranging from 1 to 5 L s^− 1 and the slope gradients ranging from 8.8% to 46.6% to simulate the soil detachment process on a road surface and to develop tools in order to calculate detachment rates occurring on that road surfaces. The results illustrate that road surfaces behave characteristically in the runoff detachment and sediment delivery process due to the difference in the bulk density and functions of agricultural soils. The soil detachment rate is closely related to flow depth, slope gradient and other hydraulic parameters such as shear stress, stream power and unit stream power. Multiple non-linear regression analyses indicate that detachment rates for all roads can be accurately predicted by power functions of flow depth and slope gradient. According to the experimental results, stream power was suggested as an indicator to estimate soil detachment rate instead of shear stress in soil erosion models. However, considering the simplicity and availability, power function of flow depth and slope gradient is also recommended to predict detachment rate on the road surfaces.     

萘对松前水稻（OryzasativaCV．生理的影响及其残留Matsumae）生长和

以松前水稻为试验材料,研究了5种浓度萘污染土壤对松前水稻生长和生理生化指标的影响,以及植物成熟期时土壤中萘的残留。结果表明：①萘浓度低于20mg·kg^-1时促进幼苗茎径、茎长、株高的生长,高浓度对其生长有显著的抑制作用。②萘胁迫对水稻叶片游离脯氨酸和蛋白质代谢均有一定的影响,且影响程度以苗期最为明显,其次是分蘖期和拔节期;水稻幼苗阶段萘的高浓度组MDA累积量极显著高于对照,水稻幼苗阶段受到膜脂过氧化影响较为显著,分蘖期次之;拔节期水稻开始新生器官,抗性较弱,萘胁迫产生的过氧化作用超过了水稻的承受范围,使SOD活性显著降低。③在试验所设萘浓度范围内,水稻各生长期叶片叶绿素和光合作用速率均呈不同的变化趋势,但是变化幅度均不超过对照的±5％,说明萘胁迫对松前水稻的光合作用没有显著影响,水稻对萘胁迫有一定的耐受性。④经过水稻一个生长周期,萘在种子中的残留量最多,其次是根部,且土壤中萘各浓度组的残留量与对照组均无显著差异;水稻根部和种子中萘的含量均随萘浓度的增加呈先增加后逐渐降低趋势,但各浓度组均高于对照组,20mg·kg^-1时均达到最大值,分别为对照组的0．37倍、4．27倍。     

不同水分条件下沙漠豆生理指标的变化

运用常规的植物生理抗旱性测定方法,对引种植物沙漠豆在不同土壤水分梯度下叶片中的可溶性糖、可溶性蛋白质、脯氨酸以及过氧化氢酶（CAT）活性,超氧化物歧化酶（SOD）活性和过氧化物酶（POD）3种保护酶等指标的变化进行研究。结果表明：1）脯氨酸含量随干旱胁迫程度的增强逐渐升高,可溶性蛋白质先降低后升高,二者之间存在相互补偿关系,可溶性糖含量呈现先升高再降低的变化趋势,表现出渗透调节物质对干旱的调节作用;2）3种保护酶活性在不同水分处理过程中变化不同,CAT活性表现为升高,SOD在中度干旱水分条件下升高,至重度干旱水分条件下则降低,POD活性的变化与SOD活性变化相反,保护酶之间相互配合协同作用维持了沙漠豆叶片细胞膜的完整性;3）丙二醛浓度随干旱胁迫程度的增强而升高,表明沙漠豆随水分不足可以通过增加渗透调节物质含量、增强保护酶活性、提高抗氧化能力,来减轻干旱胁迫的伤害。     

土壤持水特性参数与土壤质地尺度关系的联合多重分形分析

Soil water-retention characteristics at measurement scales are generally different from those at application scales, and there is scale disparity between them and soil physical properties. The relationships between two water-retention parameters, the scaling parameter related to the inverse of the air-entry pressure (αvG, cm-1) and the curve shape factor related to soil pore-size distribution (n) of the van Genuchten water-retention equation, and soil texture (sand, silt, and clay contents) were examined at multiple scales. One hundred twenty-eight undisturbed soil samples were collected from a 640-m transect located in Fuxin, China. Soil water-retention curves were measured and the van Genuchten parameters were obtained by curve fitting. The relationships between the two parameters and soil texture at the observed scale and at multiple scales were evaluated using Pearson correlation and joint multifractal analyses, respectively. The results of Pearson correlation analysis showed that the parameter αvG was significantly correlated with sand, silt, and clay contents at the observed scale. Joint multifractal analyses, however, indicated that the parameter αvG was not correlated with silt and sand contents at multiple scales. The parameter n was positively correlated with clay content at multiple scales. Sand content was significantly correlated with the parameter n at the observed scale but not at multiple scales. Clay contents were strongly correlated to both water-retention parameters because clay content was relatively low in the soil studied, indicating that water retention was dominated by clay content in the field of this study at all scales. These suggested that multiple-scale analyses were necessary to fully grasp the spatial variability of soil water-retention characteristics.     

基于Markov链地统计模型的区域土壤性质研究进展

土壤水力学性质的空间变异对于区域土壤水分溶质循环模拟研究至关重要。基于Markov链的条件模拟是一种能融合多源信息技术的地统计学模拟方法,与传统插值法和基于变异函数的条件模拟相比有诸多优势。目前,该方法在土壤水力学性质空间变异性领域的研究并未全面展开。实现区域土壤水力学模型参数的随机模拟,对于实现区域土壤水分运动和溶质运移的随机模拟,分析土壤水力学性质空间变异性对土壤水分运动和溶质运移模拟结果的影响,特别是参数采样点变化对土壤水分运动和溶质运移结果影响的不确定性等研究都有重要意义。本文旨在综述基于Markov链的地统计学模拟在土壤学相关领域的研究进展,以期为区域模拟中面临的参数获取难题提供帮助,为区域农业生产管理,水分高效利用,农田生态环境保护提供科学依据。     

流域尺度土壤厚度的模糊聚类与预测制图研究

基于土壤厚度与景观位置和特征之间的关系,运用模糊c均值聚类(FCM)方法对西苕溪流域的土壤厚度分布进行了空间预测。选取高程、坡度、平面曲率、剖面曲率、径流强度系数和地形湿度指数6个地形因子进行模糊聚类,根据相应的聚类参数将流域地形组合分为8类。利用部分调查获得的土壤剖面数据,结合样点属性和专家经验为典型区赋值,最后由加权平均得到流域土壤厚度预测图。验证结果表明,FCM方法可以对地形因子组合进行有效合理的分级,其预测精度较高,模型的稳定性较好,是一种低成本高效率的制图方法。该方法在土壤厚度预测方面具有一定的可靠性。