Hyperspectral Imaging to detect Age, Defects and Individual Nutrient Deficiency in Grapevine Leaves

TL;DR

This study demonstrates hyperspectral imaging's effectiveness in non-destructively detecting age, health status, and specific nutrient deficiencies in grapevine leaves across UV, visible, and NIR spectra.

Contribution

It introduces a comprehensive hyperspectral imaging approach with specific features for accurately identifying grapevine leaf age, health, and nutrient deficiencies.

Findings

High accuracy in distinguishing healthy and defective leaves.

Effective detection of specific nutrient deficiencies like N, K, Mg.

Hyperspectral imaging is a promising non-contact diagnostic tool.

Abstract

Hyperspectral (HS) imaging was successfully employed in the 380 nm to 1000 nm wavelength range to investigate the efficacy of detecting age, healthiness and individual nutrient deficiency of grapevine leaves collected from vineyards located in central west NSW, Australia. For age detection, the appearance of many healthy grapevine leaves has been examined. Then visually defective leaves were compared with healthy leaves. Control leaves and individual nutrient-deficient leaves (e.g. N, K and Mg) were also analysed. Several features were employed at various stages in the Ultraviolet (UV), Visible (VIS) and Near Infrared (NIR) regions to evaluate the experimental data: mean brightness, mean 1st derivative brightness, variation index, mean spectral ratio, normalised difference vegetation index (NDVI) and standard deviation (SD). Experiment results demonstrate that these features could be utilised with a high degree of effectiveness to compare age, identify unhealthy samples and not only to distinguish from control and nutrient deficiency but also to identify individual nutrient defects. Therefore, our work corroborated that HS imaging has excellent potential as a non-destructive as well as a non-contact method to detect age, healthiness and individual nutrient deficiencies of grapevine leaves