Abstract
A complex interaction involving temporal as well as spatial factors influences plant growth and development. To optimally control the environment for plant growth, an important first step is to develop crop growth models that can predict daily plant growth based on weather data, management practices, and plant genetic information. When this is accomplished, sensing data can contribute to enhanced accuracy of the plant growth model. Recent efforts to integrate plant growth models with sensing methods have provided an opportunity to optimize future plant production systems. In other words, good results require feedback from plants. The general concept is coined the ‘speaking plant’ concept. Consequently, sensors are an essential part of control systems. Machine vision can provide information about current crop status, including growth, nutrient stress and pest infestation. In this paper, current technologies are introduced and sensing system using artificial intelligence are described.
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