Frost damage to maize in northeast India: assessment and estimated loss of yield by hyperspectral proximal remote sensing

Frost in the uplands of northeast India frequently damages maize, leading to poor yields or even complete crop failure. We studied the feasibility of using reflectance spectra from
a handheld radiometer and a camera on board a drone at 80 m above the crop to assess physiological changes, differential responses of crop to nutrient managements (N, P, and NPK) and also predicted the likely losses of grain yield caused by one night’s frost damage in 90-day-old maize crop in Meghalaya, northeast India. A portable single-beam field spectroradiometer (model SVC-HR-1024) was used to measure radiation in the range of 350 to 2500 nm with varying bandwidth at 1 m above the crop. All measurements (both before and after frost) were made strictly between 11:00 and 13:00 h, when the sun was almost overhead. Similarly, a Parrot Sequoia multispectral camera sensing in four wavebands was mounted underneath a drone (DJI Matrix 600 model). We compared the measured spectra with those recorded on the same crop before the frost and also measured several biochemical constituents in the leaves on the two occasions for comparison. The frost damage increased the reflectance in the photosynthetically active visible and infrared regions with a strong peak at 2100 nm while it caused a sharp decline in the near-infrared (between 720 and 1350 nm) and shift in the red edge. It caused a decrease in the normalized difference vegetation index as measured by the radiometer from an average of 0.36 to 0.13 and a decrease from 0.5 to 0.31 as measured from the drone. The yield in frosted year was on average 870 kg ha−1 less than in the previous frost-free year on the same plots. Frost injury reduced leaf pigments (chlorophyll and carotenoids), nitrogen, and grain yield by a greater magnitude in P-stressed and NPK-deficient maize crops over N-stressed and stressfree (with NPK) plants. Spectral reflectance and vegetation indices also varied significantly. We could also assess quantitatively the crop’s loss of photosynthetic potential from the hyperspectral
reflectance measurements and from the low-flying drone. The latter technology should enable farmers to monitor and assess frost damage immediately and to predict the likely losses of
yield.