Infrared Thermal Imaging and Statistical Analysis for Plant Stress Detection and Phenotyping

 Although California is the largest agricultural-producing state in America, frequent drought conditions severely impact the amount of product produced each year. High-value crops, such as avocados (Persea americana), are extremely sensitive to water deficits. These drought conditions are also the reason why many plants are endangered. Even though plant stress is a critical factor impacting a plant’s health, current plant stress measurements involve complicated measurement systems that are both destructive to the plant and inconvenient to use for farmers and plant preservation groups. There is an urgent need for a nondestructive and convenient technique for plant drought stress detection. Three series of experiments were designed and conducted to verify the practicality of using infrared thermal imaging technique to detect plant drought stress. The experiments were conducted on three different plants: Avocado (Persea americana), a drought sensitive plant; Shaw’s Agave (Agave shawii), an endangered plant; and the Toyon (Heteromeles arbutifolia), a drought tolerant plant, under different weather and irrigating conditions. The infrared thermal images were processed, and plant surface temperatures were statistically analyzed on three different plants, which demonstrated a strong correlation between surface temperatures and plant health condition and showed the feasibility of using infrared thermal imaging technique as an efficient and convenient tool for early plant drought stress detection. Based on this infrared thermal imaging technique, a model is currently being developed to automatically statistically analyze and accurately predict early drought stress in plants.