藏北燕麦草地持续利用与撂荒对高寒草甸土壤特征的影响

为研究不同利用方式对藏北高寒草甸建植一年生燕麦（Avena sativa Linn.）人工草地的土壤理化性质及土壤细菌群落的影响,本试验于8月份植物生长旺季,在持续利用人工草地（AG）、撂荒人工草地（AC）和对照天然草地（NG）采集土壤样品,分析了土壤理化性质、土壤细菌群落组成和结构特征变化。结果表明,AG样地土壤有机质、全钾含量和pH与NG样地相比无显著性变化,土壤全氮、速效氮和速效钾含量显著降低;AC样地与NG样地相比土壤pH显著升高,土壤有机质、全氮、速效氮和速效钾含量显著降低。AG样地土壤细菌群落Chao1,Shannon和Pielou均匀度指数显著高于NG样地,AC样地酸杆菌门和变形菌门丰度显著升高。土壤理化性质是土壤细菌群落结构组成门、属相对丰度变化主要影响因子。综上所述,高寒草甸一年生燕麦人工草地长期利用应科学补充肥料,保持土壤肥力;草地撂荒需谨慎,应及时采取恢复措施避免草地发生退化。     

有关土地测绘质量问题和处理研究

文章就土地测绘的内涵解析作为切入点,浅要论述了土地测绘质量问题的影响因素,并就土地测绘质量问题影响因素的处理提出了一些浅薄的建议。以期促进我国土地测绘质量的提升。     

Evaluation of Physical Characters of soybean in the northeast region of China

以东北三省86份大豆品种资源为材料,对其与大豆加工适应性有关的物理性状进行分析评价。为东北三省大豆品质育种及选择适于不同加工用途的专用大豆品种提供依据。结果表明：黑龙江省大豆品种的平均表现是发芽率较高,蒸煮大豆硬度低,浸泡大豆的完整率高,破皮和破瓣率较低;吉林省大豆品种的平均表现是原料大豆的完整率高,障碍率低,黄度值较大,浸泡大豆硬度大,石豆率较低;辽宁省大豆品种的平均表现为百粒重大,原料大豆的障碍率高,浸泡和蒸煮大豆的硬度较大,浸泡大豆破皮和破瓣率较高,发芽率、黄度值较低。     

概念隐喻及其表达式的认知语境研究

认知语境是一种概念化了的知识结构状态,它对话语意义的理解具有重要意义。概念隐喻在认知语言学中被认为是一种认知机制或认知模式,它是对日常隐喻语言的概括和总结,它具有概括性、系统性和生成性等特点。隐喻映射是始源域和目标域之间一种本体对应的关系,而映射过程中认知语境对＂蕴涵＂选择的限定功能确证了概念隐喻及其表达式的生成及其理解过程是在认知语境的共同参与下完成的,同时认知语境对概念隐喻及其表达式的理解有一定的制约作用。     

Mining Applicable Elite Alleles of Growth Duration,Plant Height and Panicle Number per Plant by Conditional QTL Mapping in Japonica Rice

Unconditional and conditional QTL mapping were conducted for growth duration (GD), plant height (PH) and effective panicle number per plant (PN) using a recombinant inbred line (RIL) population derived from a cross between two japonica rice varieties Xiushui 79 and C Bao. The RIL population consisted of 254 lines was planted in two environments, Nanjing and Sihong, Jiangsu Province, China. Results showed that additive effects were major in all of QTLs for GD, PH and PN detected by the two methods, and the e...     

Neural network prediction of performance parameters of an inclined plate seed metering device and its reverse mapping for the determination of optimum design and operational parameters

Seed planting equipment with inclined plate seed metering devices is the most commonly used equipment for planting of peanut crop in India. For obtaining the high yield, it is very essential to drop the peanut seeds in rows maintaining accurate seed rate and seed spacing with minimum damage to seeds during metering. This mainly depends on forward speed of the planting equipment, rotary speed of the metering plate and area of cells on the plate. The relationship between these factors and the performance parameters viz., seed rate, seed spacing and percent seed damage can be established using regression analysis. But they may not be very accurate and may pose difficulty in the determination of inputs for a set of desired outputs (reverse mapping). Hence, an attempt has been made in this paper to develop the feed forward artificial neural network (ANN) models for the prediction of the performance parameters of an inclined plate seed metering device. The data were generated in the laboratory by conducting experiments on a sticky belt test stand provided with a seed metering device and an opto-electronic seed counter. The generated data was used to develop both statistical and neural network models. The performance of the developed models was compared among themselves for 4 randomly generated test cases. The results show that the ANN model predicted the performance parameters of the seed metering device better than the statistical models. In order to determine the optimum forward speed of the planting equipment, peripheral speed of the metering plate and the area of cells on the plate to obtain the recommended seed rate of 33.33 seeds/m², seed spacing of 100 mm and percent seed damage of 0.2% with 100% fill of the cells, a novel technique of reverse mapping using ANN model was followed. It was observed that the optimum forward speed of the planting equipment and optimum area of cells on the metering plate had good correlation with size of seed. Linear regression equations were developed to predict the optimum forward speed of the planting equipment and optimum area of cells on the metering plate using the size of seeds as independent parameter. The peripheral speed of the metering plate of 0.237 m/s was found to be optimum for the size of seeds in the range of 95.42-123.01 mm². However, the results need to be verified by conducting planting operation under actual field conditions.