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Image-Based Rapid Estimation of Frost Damage in Canola (Brassica napus L.)

Abstract Traditional methods of estimating frost damage to crops are labor-intensive and time-consuming. Remote sensing imagery and vegetation indices can be used for condition assessment, however, the utility of using vegetative indices in assessing frost damage specifically is not known. The objective of this study was to estimate the freezing injury using a vegetative index developed from hyperspectral imagery. Three replicates of six 6-leaf stage canola plants were subjected to a temperature of −10 °C for 6hr. The resulting frozen plants were imaged at 6 different thawing times using an imaging spectrophotometer (400-1000 nm). Normalized difference vegetation index (NDVI) and triangular vegetation index (TVI) were calculated. Contrary to expectations, NDVI values from frozen plants increased in the initial thawing treatments (1, 2 and 4hr) and then decreased at 8hr. Whereas, TVI values decreased gradually with increased duration of thawing. Furthermore, when compared to NDVI, TVI clearly differentiated frozen from control plants and within the freezing treatments. The differential modes of response of the indices to post-freezing reflectance changes is the possible reason. These results suggest that with recent advancements in low altitude remote sensing in the areas of spectral, spatial and temporal resolution, early estimation of frost damage is possible.