葉子的葉綠體是進行光合作用的關鍵，行光合作用會產生生長和發育所必需的碳水化合物。因此，植物光合作用是自然界中碳水化合物和氧氣的主要來源，也是我們人類生存的基礎。而作物產量與幾個主要因素有關，包括光合作用效率，吸水和利用效率，肥料吸收效率，抗病蟲害和溫度適應性。由於氣候變化和人力減少，作物產量下降。因此，極端氣候下的作物栽培和增產是需要解決的重要問題。通過智慧農業減少水、肥料和農藥的數量，以實現更少的水，更少的肥料、農藥、和更少的疾病。作物水生理團隊向人工智能團隊提供各種不同的傳感器數據，以開發智慧農業預警水系統。在建立系統時，我們使用特徵選擇來構建預測模型。最後選擇的五個特徵可以獲得最佳效能。

The key to plant photosynthesis using sunlight is the chloroplast of the leaves, which produces the carbohydrates necessary for growth and development. Therefore, plant photosynthesis is the main source of carbohydrates and oxygen in nature, and it is also the basis for our human survival. And crop yield is related to several major factors, including photosynthesis efficiency, water absorption and utilization efficiency, fertilizer absorption efficiency, resistance to pests and diseases, and temperature adaptability. Crop yield declines due to climate change and manpower reduction. Therefore, crop cultivation and increased yield in extreme climates are important issues to be solved. To reduce the amount of water, fertilizers, and pesticides through smart farming to achieve less water, less fertilizer, pesticides, and less disease. We collected a variety of different sensor data to develop wisdom irrigation system. The feature selection and artificial intelligence approaches were used to build the prediction model. Finally, we chosen five significant features for our system.

人工智慧、植物光合作用、作物產量

Artificial Intelligence, Plant Photosynthesis, Crop Yield