加速广义Laguerre多项式级数的Laplace变换的数值反演方法

本文利用Levin t-变换迭代法，对加速广义Laguerre多项式级数，提出了一种新的Laplace变换的数值反演方法，这种方法在精度上和数值稳定性上的效果都较好。     

两种一年生植物在替代试验中的相互竞争关系

（1）用替代试验研究了燕麦（Aneva sativa）和箭舌豌豆（Vicia sativa）在混播中的竞争相互作用。为了攻混播比例对两种植物在混播条件下的行为影响，田间试验设为5个混播总密度和5种混播比例，共了5次。（2）方差分析表明，相对总生物量（RYT）和竞争平衡指数（CBI）对总密度，混播比例和生长时间的反应敏感。总密度对RYT和CBI的影响高度显著，在大多数情况下，混播比例对RYT和CBI的影响不显著。（3）本文研究的结果表明，持续时间对RYT和CBI很强的影响，在第1次测定时，RYT值接近1而BI值接近0，这一事实表明，种间无竞争或互惠作用。而在生长旺盛期，种间竞争较为剧烈。（4）本研究结果表明，箭舌豌豆的生长严惩受到燕麦的抑制作用，这说明箭舌豌豆在与燕麦混播时表现为竞争上的弱者。     

小麦矮秆育种中性状间关系的多元分析

以7个株高梯度系列的35个系统及5个亲本品种为材料,采用典范分析和逐步回归分析研究了株高及其构成因子与产量因子、产量生理性状间的关系。结果表明:①株高因子通过产量生理性状影响产量因子,一定的生物学产量是获得高产的基础。②矮秆品种的高化对提高产量、千粒重和收获指数有利,对蛋白质含量的影响不明显;高秆品种矮化能显著提高收获指数,对籽粒的蛋白质含量影响不大。③在主要性状符合育种目标的前提下,选择倒二节间较长、第一和第二叶间距略长、穗颈和穗部较长的类型可能对提高产量有利。     

Trends in NE Atlantic landings (southern Portugal): identifying the relative importance of fisheries and environmental variables

Time series of commercial landings from the Algarve (southern Portugal) from 1982 to 1999 were analyzed using min/max autocorrelation factor analysis (MAFA) and dynamic factor analysis (DFA). These techniques were used to identify trends and explore the relationships between the response variables (annual landings of 12 species) and explanatory variables [sea surface temperature, rainfall, an upwelling index, Guadiana river (south‐east Portugal) flow, the North Atlantic oscillation, the number of licensed fishing vessels and the number of commercial fishermen]. Landings were more highly correlated with non‐lagged environmental variables and in particular with Guadiana river flow. Both techniques gave coherent results, with the most important trend being a steady decline over time. A DFA model with two explanatory variables (Guadiana river flow and number of fishermen) and three common trends (smoothing functions over time) gave good fits to 10 of the 12 species. Results of other models indicated that river flow is the more important explanatory variable in this model. Changes in the mean flow and discharge regime of the Guadiana river resulting from the construction of the Alqueva dam, completed in 2002, are therefore likely to have a significant and deleterious impact on Algarve fisheries landings.     

The effect of populations of Xanthomonas campestris pv. phaseoli in bean reproductive tissues on seed infection of resistant and susceptible bean genotypes

Surface and internal populations of Xanthomonas campestris pv. phaseoli, causal agent of common bacterial blight of bean, on and in flower buds, blossoms and pods of seven bean (Phaseolus vulgaris) genotypes were studied. Bean plants were grown in the field and artificially inoculated at the seedling stage (18 days old). The pathogen was recovered in high numbers from flower buds, blossoms, pods and seed of both resistant and susceptible bean genotypes. Significant differences (P = 0.05) in population levels of X. c. pv. phaseoli between stages of reproductive tissue development were observed. Infected seed from resistant bean genotypes had no visible symptoms. Such seed may play an important role in the epidemiology of common bacterial blight because they are difficult to detect and may occur at low frequency in seed lots, as was the case in the current study.     

Variation and distribution of virulence phenotypes of Bremia lactucae in natural populations of Lactuca serriola

During 1997–2000 the virulence variation and distribution of virulence phenotypes of Bremia lactucae (lettuce downy mildew) in natural populations of Lactuca serriola (prickly lettuce) were studied. Altogether 139 isolates of B. lactucae originating from the Czech Republic, France and Germany were examined for the presence of 27 virulence factors (v-factors) and their combinations. In the Czech population, 37 different v-phenotypes (P1–P37) of B. lactucae were found to occur on L. serriola . Most v-phenotypes were characterized by v-factors that match resistance ( Dm genes/R-factors) carried by L. serriola . A wide diversity of v-phenotypes was recorded every year, but most were rare and did not reappear in other populations of B. lactucae . The three v-phenotypes P21, P28 and P29 were most frequent and widely distributed. There was variation both between spatially isolated populations and within populations of the pathogen. Geographic differences in virulence were found for the southern parts of Moravia, where the phenotypic composition of pathogen populations was completely different from the remaining part of the area investigated. However, some populations had v-phenotypes similar to those of spatially distant populations in Moravia.     

植物化感作用影响因素的再认识

土壤养分、酶、微生物、本底特性,根茬还田、水分、植物根系、种植体系和种植模式与化感作用的互作关系,表明这些因子可通过对土壤养分有效性、微生物种群结构、土壤酶活性和化感物质浓度的影响而对化感作用产生直接或间接影响,这些可为通过化感作用途径构建高效农田生态系统提供新的思路.     

土壤pH值对极小种群毛枝五针松生理特性的影响

幼苗建成期是毛枝五针松(Pinus wangii)天然更新的关键阶段,为找出影响毛枝五针松幼苗存活的关键生态因子,采用植物生理学方法,研究在7个酸碱度土壤培育下,毛枝五针松松针超氧化物歧化酶(SOD)、过氧化物酶活性(POD)活性和脯氨酸、可溶性糖质量分数及丙二醛(MDA)摩尔质量浓度的变化。结果表明:毛枝五针松在弱碱土壤中抗逆性更强,形态观察得知其在弱碱性土壤中生长更好;生理指标测定结果表明,土壤在p H=7.69~8.42时最适宜毛枝五针松幼苗的生长发育。     

极小种群野生植物八蕊单室茱萸的种群状况研究

八蕊单室茱萸为云南省特有的极小种群野生植物和濒危物种。通过查阅相关文献并结合访问调查,确定八蕊单室茱萸可能分布的区域,开展种群资源调查。结果显示:八蕊单室茱萸目前仅在普洱市和西双版纳州有10个天然种群,其种群规模已低于最小可存活种群,属极小种群野生植物和濒危物种,亟需开展保护工作。生境破坏和生境片段化是导致八蕊单室茱单室茱萸濒危的人为因素。提出收集种质资源、营建和管护近地保护种群、建立迁地和回归种群等保育建议。     

Simulation of future dissolved oxygen distribution in pond culture based on sliding window-temporal convolutional network and trend surface analysis

Dissolved oxygen (DO) is a key ecological factor to measure the quality of water in the aquaculture. As the pond water body is affected by the breeding environment, the spatial distribution of DO shows a certain law in the entire pond. Therefore, to simulate the distribution of DO in aquaculture waters and grasp the temporal and spatial variation of DO is the key to achieving precise regulation of DO. For this purpose, this paper proposed a method for simulating the temporal and spatial distribution of DO in pond culture based on a sliding window-temporal convolutional network together with trend surface analysis (SW-TCN-TSA). This paper first utilized SW to construct DO data sets with different prediction durations, and then used the improved TCN model to realize one-dimensional time series prediction for DO at single monitoring point. Based on the prediction results of DO, a TSA method was performed on the predicted values of DO at the extreme moments of all discrete monitoring points, so as to realize the simulation of the temporal and spatial distribution of DO in the pond. Experimental results show that the SW-TCN model has better prediction performance for one-dimensional time series prediction of DO. Compared with traditional deep networks, such as CNN, GRU, LSTM, CNN-GRU and CNN-LSTM, the values of evaluation indicators (MSE, MAE and RMSE) have been greatly improved. In the process of trend surface fitting, all fitting R² of DO at different water depths are higher than 0.9, indicating that the TSA can accurately reflect the temporal and spatial distribution of DO. This method can provide a basis for the prediction and early warning of DO in the three-dimensional space of the pond and has high practicability in aquaculture.