Forecasting infections of the red rot disease on Porphyra yezoensis Ueda (Rhodophyta) cultivation farms

Pythium porphyrae is a fungal pathogen responsible for red rot disease of the seaweed Porphyra (Rhodophyta). Infection forecasts of Porphyra by P. porphyrae were estimated from the epidemiological observations of Porphyra thalli and numbers of zoospore of P. porphyrae in laboratory and cultivation areas. Four features of forecasting infections were determined by relating zoospore concentrations to the incidence of thallus infection; infection (in more than 1000 zoospores L⁻¹), microscopic infection [less than 2 mm in diameter of lesion (in from 2000 to 3000 zoospores L⁻¹)], macroscopic infection [more than 2 mm in diameter of lesion (in from 3000 to 4000 zoospores L⁻¹), and thallus disintegration (in more than 4000 zoospores L⁻¹). High zoospore concentrations led to more infection. The tendency that zoospore concentration of P. porphyrae increased with the rate of infection of Porphyra thalli was generally observed in forecasting infections in both the laboratory and in cultivation areas. Based on the Porphyra cultivation areas, the accuracy and consistency of forecasting infections suggest that this method could be employed to manage and control red rot disease.     

Towards numerical forecasting of long-range air transport of birch pollen: theoretical considerations and a feasibility study

This paper considers the feasibility of numerical simulation of large-scale atmospheric transport of allergenic pollen. It is shown that at least small grains, such as birch pollen, can stay in the air for a few days, which leads to a characteristic scale for their transport of ∼10³ km. The analytical consideration confirmed the applicability of existing dispersion models to the pollen transport task and provided some reference parameterizations of the key processes, including dry and wet deposition. The results were applied to the Finnish Emergency Dispersion Modelling System (SILAM), which was then used to analyze pollen transport to Finland during spring time in 2002–2004. Solutions of the inverse problems (source apportionment) showed that the main source areas, from which the birch flowering can affect Finnish territory, are the Baltic States, Russia, Germany, Poland, and Sweden—depending on the particular meteorological situation. Actual forecasting of pollen dispersion required a birch forest map of Europe and a unified European model for birch flowering, both of which were nonexistent before this study. A map was compiled from the national forest inventories of Western Europe and satellite images of broadleaf forests. The flowering model was based on the mean climatological dates for the onset of birch forests rather than conditions of any specific year. Utilization of probability forecasting somewhat alleviated the problem, but the development of a European-wide flowering model remains the main obstacle for real-time forecasting of large-scale pollen distribution.     

粉虱类害虫的监测预警与可持续治理技术透视

针对烟粉虱Bemisia tabaci（Gennadius）、温室白粉虱Trialeurodes vaporariorum（Westwood）、黑刺粉虱Aleurocanthus spiniferus（Quaintance）、桑粉虱Pealius mori（Takahashi）、禾粉虱Aleurocybotus indicus David etSubramaniam等粉虱害虫在我国暴发危害的现状,公益性行业科研专项＂粉虱类害虫可持续治理技术研究与集成示范＂项目组在华南、华东、华北、华中和西南等地区开展了粉虱类害虫的调查、监测、预警以及综合防控技术研究集成与示范。结果表明,烟粉虱在我国的发生区域超过20个省份,温室白粉虱在华北和西南地区,黑刺粉虱在华南、华东和西南地区也分布较广,桑粉虱在我国南方桑植区危害严重,禾粉虱在福建省闽东稻区发生为害逐年严重。利用mt COI DNA测序、SCAR技术和CAPS等技术对B和Q型烟粉虱的鉴定结果显示,Q型烟粉虱在我国的分布范围正在不断扩大。通过Maxent预测模型和GIS技术,预测了烟粉虱在我国的适生区、自然越冬北线和不同地区的发生世代数量。对烟粉虱的抗药性监测结果表明,阿维菌素和烯啶虫胺是目前华北地区防治烟粉虱较为理想的药剂,而对联苯菊酯、噻虫嗪、啶虫脒和吡虫啉等药剂均产生了不同程度的抗药性。研究了苘麻诱集、黄板诱杀、天敌昆虫和病原微生物对粉虱类害虫的控制作用,并在华南、华东、华北、华中和西南等地区建立了12个示范基地,分别在不同地区开展了粉虱类害虫的综合防治技术的示范和推广,累计印刷技术宣传手册12.4万份,培训各类农民和基层农技人员5.43万人次,累计示范面积4.3千公顷次,技术辐射超过4万公顷次,取得了显著的经济、社会和生态效益。     

外来入侵害虫西花蓟马防控技术研究与示范

针对入侵害虫西花蓟马Frankliniella occidentalis(Pergande)在我国部分地区暴发成灾的形势,公益性行业科研专项"外来入侵害虫西花蓟马防控技术研究与示范"项目组在除西藏、台湾、香港和澳门以外的30个省、区和直辖市开展了西花蓟马的调查、监测、预警和综合防控技术研究与示范。结果表明西花蓟马在北京、云南、浙江、山东等14个省市发生危害,尤以云南和北京两地最为严重,在全国呈快速蔓延趋势。明确了西花蓟马在我国的成灾机制;建立了西花蓟马高效诱捕技术;筛选出4种对西花蓟马具有显著控害潜力的本土天敌昆虫及病原微生物;筛选出5种对西花蓟马高效、对环境友好的防治药剂;明确西花蓟马重要发生区域北京和云南种群对主要化学药剂的抗性和机制;分别组建了基于农业措施防治、色板与引诱剂应用的引诱技术、生物防治和高效环保化学农药综合应用的10套西花蓟马防控技术体系,在我国北京、云南、山东和浙江等西花蓟马主要发生区域累计推广面积2.65万公顷,有效控制了西花蓟马的为害和扩散蔓延。     

The successful quest for oral factor Xa inhibitors; learnings for all of medicinal chemistry?

The medicinal chemistry of oral small molecule factor Xa inhibitors is discussed, highlighting key advances that led to clinical candidates and the first licensed medicines. Identification of neutral ligands for the primary specificity pocket was a key discovery; capitalised upon by structure based design and combinatorial methods to deliver many variations on the theme; but it was good medicinal chemistry practice, in the optimisation of physical properties, which ultimately delivered efficacious compounds with adequate oral exposure. As a retrospective appraisal, representative compounds were profiled using the more contemporary concepts of Ligand Efficiency and Property Forecast Indices; which gave clear indications of the value of these principles.     

二点委夜蛾卵巢发育分级及在预测预报中的应用

对室内饲养的二点委夜蛾Athelis lepigone(Moschler)雌成虫分时段进行解剖,观察其卵巢的结构及发育进程。结果显示二点委夜蛾具有1对卵巢,各由4个卵巢小管组成。发育进程可分为5个阶段:透明期、卵黄沉积期、成熟待产期、产卵盛期和产卵末期。河北省石家庄地区2011年7月下旬至8月上旬田间卵巢发育的监测结果显示,Ⅰ级卵巢在整个发生期所占比例较高,Ⅳ级卵巢所占比例较低,推测其下一代幼虫的发生量将较低,并与田间调查结果吻合,因此卵巢解剖分级法可以用于二点委夜蛾的预测预报工作。     

广州地区冬季鱼塘水温特征及其预测预报

冬季水温对耐寒性较差的热带、亚热带鱼类的安全越冬有重要影响。本文根据鱼塘水温和附近气象站气温观测资料 ,研究了广州地区冬季鱼塘水温特征及其预测模型。结果表明 ,与气温相比 ,鱼塘水温日振幅较小 ,日最高温度出现时间滞后 ,这种特征在逐时温度和日平均温度上表现得都非常明显 ;晴天条件下水温的日变化远大于阴天 ;随水层深度的增加 ,水温日振幅逐渐减小 ,位相滞后也愈加明显。水温与气温的交叉相关分析表明 ,水温与当日、前一日、前二日、前三日的气温有显著的相关关系 ,与前四日、前五日的关系已不明显。利用逐步回归分析 ,建立了以气温为自变量的各水层水温预报模型。各模型的回归效果都达到了显著水平 ,平均绝对误差均在 0 5℃以内 ,平均相对误差均在 1 0 %以内 ,具有较高的精度 ,可用于冬季鱼塘水温的预报。     

A new approach to consider the pollen variable in forecasting yield models

Methods for forecasting harvest yields have been improved considerably in the last 20 years with the development of new data survey (remote sensing) and statistical techniques. One of these methods, based on pollen release in the atmosphere, is especially important for anemophilous species such as olive. The aim of the present work is to use a different approach to forecast the olive harvest by considering the pollen variable as “endogenous” because it is involved in the consequential processes from the formation of pollen to fruiting, the complex of which determines, more or less, the final production. Unlike models built upon a single equation (multiple linear regression analysis), the proposed estimate, based on an incomplete system of equations, recovers the consistency associated with the inference of parameters while avoiding the errors of “over-estimation.” The study, based on 17 years of data considers the quantity of olive pollen monitored and the relative annual olive production in addition to climatic, agronomic, and pathological variables associated with production. The harvest forecast provides the possibility for planning and optimizing the various stages of olive production from cultivation to distribution, including sound management of the olive supply.

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Une nouvelle approche pour considérer la variable pollen dans les modèles de prévision des rendement de récolte

Résumé  Pendant les vingt dernières années les méthodes de prévision des rendements de récolte ont été considérablement améliorées grace au développement de nouvelles techniques statistiques et d’ enquête des données (télédétection). Parmi ces méthodes celle basée sur l’émission du pollen dans l’atmosphère se révèle particulièrement importante pour les espèces anémophiles comme l’olivier. Le but de ce travail est celui d’arriver à employer une méthode différente dans la prévision des rendements de récolte de l’olivier, le tout en considérant comme “endogène” la variable pollen. Ce dernier est, en effect, impliqué dans les processus d’évolution qui vont de sa formation à la fructification, de manière à déterminer la production finale. Contrairement aux modèles établis sur une équation simple (analyse multiple de régression linéaire), l’évaluation proposée, basée sur un système inachevé d’équations, récupère la consistance connexe à l’ inférence des paramètres tout en évitant les erreurs de “surestimation”. L’étude, basée sur dix-sept ans de données, considère la quantité de pollen d’olivier détectée et conséquemment la production oléicole annuelle, outre aux variables climatiques, agronomiques et pathologiques liées à la production. Les modèles de prévision offrent la possibilité de rationaliser les différentes phases de la filière oléicole en optimisant les procédés, de la production à la distribution, y compris la gestion rationnelle des stocks.