Precise Sensing of Leaf Temperatures for Smart Farm Applications

Abstract

Leaf temperature represents the mixed effects of solar radiation, temperature, and CO2 enrichment on the potential production of greenhouse vegetables. However, smart farm applications that monitor and account for changes in leaf temperature are limited. This study developed new hardware and software components for leaf temperature sensing integrated into a conventional smart farm system. We demonstrated a new system to monitor leaf temperatures and improve crop yield at two greenhouse tomato and strawberry farms in South Korea. We observed a rapid decline in leaf temperature at both farms when the indoor air temperature decreased. This pattern often corresponds to stagnant CO2 assimilation. The results suggest that leaf temperature sensing is practical for slow aeration and heating that is required to optimize photosynthetic efficiency, especially in the morning and when leaf temperatures become high (over 25 °C). Specifically, smart farm implementation with leaf temperature sensing increased the yield of tomatoes by 28–43%. Furthermore, our study highlights the need to develop leaf temperature models for smart greenhouse farming that interact with nutrient and water supplies.