Changes in Spectral Characteristics of Rice Canopy Infested with Brown Planthopper and Leaffolder

Abstract

Potted experiments of rice (Oryza sativa L.) plants were conducted to produce various scales of brown planthopper [Nilaparvata lugens (Stål), Homoptera:Delphacidae] and leaffolder [Cnaphalocrosis medinalis Guenee (Lep., Pyralidae)] infestations, respectively, for canopy hyperspectral reflectance measurements, and then to identify spectral characteristics (SCs) associated with insect infestations leading to the establishment of spectral models for severity assessment. By linear correlation intensity analysis, correlation coefficients (r) along the spectral domain of 350 to 2400 nm were determined and narrow bands related to infestation severity were selected as SCs. The reflectance at green light (490–560 nm) maximum (RGREEN), red light (640–740 nm) minimum (RRED), and near‐infrared (740–1300 nm) peak (RNIR) were also considered. For canopies infested with brown planthopper, r value at 426 nm was the highest (r = 0.878**). Among the calculated spectral indices using two SCs, the determination coefficient of RNIR/RRED ratio was the highest (R2 = 0.922, P < 0.001). For leaffolder infested canopies, the most negative r value located at 757 nm (r = −0.613*) in active tillering stage but shifted to 445 nm (r = −0.928**) in heading stage. The index RNIR − RRED in the active tillering increased R2 value to 0.422 (P < 0.001), while no increase in R2 was found in the examined SIs in heading stage. Models with more than two SCs yielded from multiple linear regression analysis exhibited a further improvement for discriminating infestation severity.

Developing Two Spectral Disease Indices for Detection of Wheat Leaf Rust (Pucciniatriticina)

“…Mohammad et al showed that the visible and infrared regions of the electromagnetic spectra provide the maximum information on physiological stress levels in an affected plant [14]. Some of the wavelengths specific to a disease can be used to detect plant disease [15].Optimum spectral ranges have been suggested to detect different disease; 425, 685 and 735 nm to detect citrus canker [16], 737-925 nm to detect brown plant hopper disease of rice [17], 426 nm for brown plant hopper and leaf folder infestation of rice [18], and 800 to 1100 nm to identify leaf miner damage of tomato [19].…”

Assessment of the severity of bacterial leaf blight in rice using canopy hyperspectral reflectance

“…Reflectances of agriculture crops in the visible and infrared regions have been studied in order to estimate different crop properties and to assess growth status of the crop (Carter and Knapp 2001;Kumar et al 2001;Yang and Chen 2004;Yang et al 2007). Most healthy crop canopies generally have large reflectances in the near-infrared region (700-1300 nm; NIR) and smaller reflectances in the photosynthetically active region (400-700 nm; PAR) depending on photosynthetic activity (Hall et al 2002;Yang and Chen 2004).…”

Integrated pest management for sustainable rice cultivation: a holistic approach

“…However, without knowledge of the frequencies and spatial extent of such losses, such information is of little value. Recent research has attempted to improve the situation by developing technologies to better detect pests including using remote sensing applications (Lamb and Brown, 2001;Yang et al, 2007). It will be necessary to continually update damage thresholds and estimated yield losses as climates and crop management practices change and because different rice varieties often have specific responses to pest attack (see Section 11).…”