Abstract:
Maize, a vital global crop, faces numerous challenges, including outbreaks. This study explores the use of spectral
vegetation indices for the early detection of maize diseases in individual leaves based on crop phenology at the
vegetative, tasselling, and maturity stages. The research was conducted in rural areas of Giyani in the Limpopo
province, South Africa, where smallholder farmers heavily rely on maize production for sustenance. Fungal and
viral diseases pose significant threats to maize crops, necessitating precise and timely disease detection methods.
Hyperspectral remote sensing, with its ability to capture detailed spectral information, offers a promising solution. The study analysed spectral reflectance data collected from healthy and diseased maize leaves. Various
vegetation indices derived from spectral signatures, including the Normalized difference vegetation index
(NDVI), Anthocyanin Reflectance Index (ARI), photochemical Reflectance Index (PRI), and Carotenoid Reflectance Index (CRI) were investigated for their ability to show disease-related spectral variations. The results
indicated that during the tasselling stage, the spectral differences had minimum absorption in the blue region.
However, a distinct shift in spectral reflectance was observed during the vegetative stage with 70 % increase in
reflectance. First derivative reflectance analysis revealed peaks at approximately 715 nm and 722 nm, which
were useful in the discrimination of the different growth stages. Generalized Linear Models (GLM) with binomial
link functions and Akaike Information Criterion (AIC) showed that individual vegetation indices performed
equally well. NDVI (P<0.001) and CRI (P<0.000) showed the lowest AIC values across all growth stages, suggesting their potential as effective disease indicators. These findings underscores the significance of employing
remote sensing technology and spectral analysis as essential tools in the endeavours to tackle the difficulties
encountered by maize growers, especially those operating small-scale farms, and to advance sustainable farming
practices and ensure food security
