Spatial–spectral processing strategies for detection of salinity effects in cauliflower, aubergine and kohlrabi

Hyperspectral images and spectroradiometer measurements were taken from cauliflower (Brassica oleracea, Botrytis group), aubergine (Solanum melongena) and kohlrabi (Brassica oleracea, Gongylodes group) plants in a controlled experiment. Plants were grown in media with sodium chloride (NaCl) concentrations between 30 and 150 mmol. Spectral and spatial processing techniques were developed to assess the ability to distinguish between plants exposed to various levels of salinity stress. Local autocorrelation analysis was used to detect the spatial patterns that characterise the effects of salinity on crop canopy. This analysis was applied on a vegetation index in the spectral range of 435–554 nm, the green indigo ratio (GIR) index. The processing strategies that were developed were able to distinguish three levels of salinity effects. The strategy based on a combined spatial–spectral index yielded the most consistent results with average total accuracy of 62%, whereas accuracies obtained with known spectral vegetation indices were 29%. The presented method may be implemented in other cases of vegetation stresses where symptoms are characterised by patchiness and can be imaged, not necessarily in the visible spectral range (400–750 nm).

► The effect of salinity in three crops was detected using hyper spectral images. ►Spatial–spectral indices were extracted from hyperspectral images. ► Local autocorrelation analysis revealed spatial patterns of salinity on crop canopy. ► The salinity effect was expressed in the spatial distribution of index fluctuations.