Nutrient status plays a pivotal role in plant growth and productivity. Monitoring nutrient status is crucial for crop managers to inform their decision on applying adequate doses to balance plant production against economic loses and environmental effects for sustainable agriculture.
The assessment of nutrient status based on the chemical analysis of plant tissue is often used by crop managers to quantify nutrient concentration. However, the method is not efficient nor an affordable approach for the continuous monitoring of nutrient status at the entire farm level, especially considering large seasonal and within-field spatial variations. In this context, remote sensing using imaging spectroscopy offers effective and repeatable solutions for nutrient and water stress detection and has enormous potentials to inform fertilizer and irrigation management.
Physically-based radiative transfer models can be used to derive plant physiological traits, which are closely related to nutrient content. Solar-Induced Fluorescence (SIF) has a strong link to photosynthetic status and productivity, and it’s a proxy of plant stress. Homogenous crops like wheat have been well studied in terms of estimating nutrient status by combining SIF and plant traits derived from physical models. However, studies in fruit trees are rare due to the difficulties of properly assess the structural complexity of tree crown, varying leaf density and soil background effects.
This research aims to explore the assessment of water and nutrient status using SIF quantified from airborne hyperspectral imagery and plant physiological traits derived from the inversion of physical radiative transfer models and its connection with yield reduction in almond trees. Methods for leaf and canopy trait retrievals will be evaluated along with tree-level yield data, aiming at developing models for a wide range of water stress and nutrient levels. This research will contribute to the large-area mapping of nutrient and water status of individual trees, which in turn will inform fertilizer and irrigation decisions for rapid and precise plant management. The improvement of monitoring capabilities and the optimal use of fertilizer and water input are crucial to maintain a sustainable farm management.
Department of Infrastructure Engineering
Faculty of Engineering and Information Technology
University of Melbourne