Integrating Spectroscopy with Potato Disease Management

Abstract

Spectral phenotyping is an efficient method for the nondestructive characterization of plant biochemical and physiological status. We examined the ability of a full range (350 to 2,500 nm) of foliar spectral data to (i) detect Potato virus Y (PVY) and physiological effects of the disease in visually asymptomatic leaves, (ii) classify different strains of PVY, and (iii) identify specific potato cultivars. Across cultivars, foliar spectral profiles of PVY-infected leaves were statistically different (F = 96.1, P ≤ 0.001) from noninfected leaves. Partial least-squares discriminate analysis (PLS-DA) accurately classified leaves as PVY infected (validation κ = 0.73) and the shortwave infrared spectral regions displayed the strongest correlations with infection status. Although spectral profiles of different PVY strains were statistically different (F = 6.4, P ≤ 0.001), PLS-DA did not classify different strains well (validation κ = 0.12). Spectroscopic retrievals revealed that PVY infection decreased photosynthetic capacity and increased leaf lignin content. Spectral profiles of potato cultivars also differed (F = 9.2, P ≤ 0.001); whereas average spectral classification was high (validation κ = 0.76), the accuracy of classification varied among cultivars. Our study expands the current knowledge base by (i) identifying disease presence before the onset of visual symptoms, (ii) providing specific biochemical and physiological responses to disease infection, and (iii) discriminating between multiple cultivars within a single plant species.