早疫病預報系統對檢測西班牙西北部馬鈴薯作物首發癥狀的適用性研究
近年來，早疫病的流行頻繁導致馬鈴薯作物嚴重減產。當天氣條件有利時，這種真菌病會迅速發展，迫使農民使用殺菌劑。利米亞是西班牙最大的馬鈴薯生產區之一。通常，早期疫病流行是使用預先制定的日程表來控制的。這種策略成本高昂，并且會影響農業區的環境。目前還沒有農民使用決策支持系統來管理早疫病。因此，本研究的目的是根據植物或/和病原體要求和天氣條件評估不同的早疫病預測模型，以檢查它們對預測早疫病最初癥狀的適用性，這是確定第一種殺菌劑的時間所必需的應用。為此，在五個作物季節監測天氣、物候和疾病癥狀。在植物出苗后 37 至 40 天，在開花期開始出現第一個早疫病癥狀�；谥参锏念A測模型提供了最好的結果。具體而言，具有 1.4 個風險單位和成長度天數（361 個累積單位）的 Wang-Engel 模型提供了最佳預測�；诓≡w的模型顯示出保守的預測，而結合植物和病原體特征的模型預測第一次早疫病襲擊明顯較晚。
五個作物季節的天氣參數和物候變化
Suitability of Early Blight Forecasting Systems for Detecting First Symptoms in Potato Crops of NW Spain
Abstract: In recent years, early blight epidemics have been frequently causing important yield loses
in potato crop. This fungal disease develops quickly when weather conditions are favorable, forcing
the use of fungicides by farmers. A Limia is one of the largest areas for potato production in Spain.
Usually, early blight epidemics are controlled using pre-established schedule calendars. This strategy is expensive and can affect the environment of agricultural areas. Decision support systems are not currently in place to be used by farmers for managing early blight. Thus, the objective of this research was to evaluate different early blight forecasting models based on plant or/and pathogen requirements and weather conditions to check their suitability for predicting the first symptoms of early blight, which is necessary to determine the timings of the first fungicide application. For this, weather, phenology and symptomatology of disease were monitored throughout five crop seasons. The first early blight symptoms appeared starting the flowering stage, between 37 and 40 days after emergence of plants. The forecasting models that were based on plants offered the best results. Specifically, the Wang-Engel model, with 1.4 risk units and Growing Degree-Days (361 cumulative units) offeredthe best prediction. The pathogen-based models showed a conservative forecast, whereas the models that integrated both plant and pathogen features forecasted the first early blight attack markedly later.
Pessl植物生理生態監測系統的全套監測系統和在線平臺FieldClimate適用于所有氣候區，可用于各種行業和各種用途——從農業到研究、水文、氣象、洪水警報等。iMetos植物生理生態監測系統已經成為一個全球品牌，使用持續時間更長，性能更好，是通用的天氣監測設備，具有早期識別和警報功能（有SMS手機提醒功能）；可以用來計劃、控制和管理復雜的獨立氣象過程。該監測系統專為不同氣候區域的多種任務而設計。其可以安裝多達600個傳感器，如土壤和空氣濕度、溫度、降雨、風速、風向、葉片 濕度、總體輻射等傳感器。
Pessl植物生理生態監測系統的數據采集工作站可以將這些數據無線傳輸到安全的互聯網數據庫上。該數據庫是優秀的數據存儲和處理平臺。用戶獲得登錄密碼后，可以從世界任何地方的互聯網終端登錄并獲得這些數據、報告和圖表。測量的信息來源于傳感器所在的位置。使用者可以從網站上一個區域可輸入或修改閾值和電話號碼。操作無需專門軟件。
Pessl植物生理生態監測系統僅需要有效的GPRS協議用于數據傳輸，在站點所在處也需要網絡的充分覆蓋。該系統是一組多功能、模塊化配置的系統，運行完全免維護。該工作站采用太陽能充電電池。工作站可以連接多種傳感器。即插即用模式便于工作站擴展傳感器數目。
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