過去農業仰賴農民長久的種植經驗判斷農作物狀態，但人力有限與無法全時管理，進而影響農作物品質。因此在農業勞動人口下降的環境下，智慧化與自動化監控系統的崛起備受矚目。本研究開發菇類微型溫室監控系統，並透過LabVIEW與NI cDAQ做硬體控制與程式環境編譯。在論文中詳細介紹LabVIEW程式設計的實現方法，且結合菇農的使用習慣打造人性化的人機介面監控，可隨時調整溫室的環境參數。不僅使用者能即時在別處觀看溫室情形，也能利用相機定時捕捉農作物狀況與並定時紀錄各項參數，以便農民評估歷史資料。本研究除了提出微型溫室監控架構外，也分析各項參數如溫度、濕度、二氧化碳間的交互影響。
在眾多農業資料分析方法當中，本研究利用實驗設計(DOE)對生長資料進行統計分析，討論二氧化碳濃度與維持時間對杏鮑菇子實體發育的影響，並對杏鮑菇重量(產量)、高度、粗細比與菇帽直徑做評估。在兩項實驗中(粗細比與重量)發現「二氧化碳濃度」影響力小於誤差，而「維持時間」都有一定的顯著性。

In the past, agriculture relied on farmers’ planting experience to judge the status of crops, but the quality of crops was affected by the limited labor and inability to manage the farm. As the result, the rise of intelligence and automated monitoring systems has attracted a great deal of attention. This study built the miniature mushroom greenhouse monitoring system by using LabVIEW and NIcDAQ as the hardware control environment. In this thesis, the implemenataion method of LabVIEW programming is introduced in detail. The user-friendly human-machine interface was designed based on the habits of mushroom farmers to adjust the environmental parameters. Not only the user can monitor the greenhouse environment remotely, but can use the camera to capture the condition of the crops and record the parameter values periodically. In addition to developing the monitoring architecture of the greenhouse, the interactions between various internal parameters such as temperature, humidity, and carbon dioxide (CO_2) were analyzed.
Of the many methods for analyzing the agricultural data, this study used " Experimental design " for the statistical analysis. The influence of CO_2 concentration and sustain time on the growth of the king oyster mushroom was discussed, and the weight, height, thickness ratio, and cap diameter of the mushroom were evaluated. In two experiments (thickness ratio and weight), it was found that the influence of "CO_2 concentration" was less than the error, and the "sustain time" had certain significance.

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