Noninvasive detection of plant parasitic nematodes using hyperspectral and other remote sensing systems

Abstract More than 4100 nematode species have been identified as plant parasites, but only a small proportion of these cause substantial economic damage in agricultural crop production, estimated at up to US$157 billion annually. The most damage is caused by cyst nematodes of the Globodera and Heterodera genera, and root-knot nematodes of the genus Meloidogyne. In forestry, the pinewood nematode, Bursaphelenchus xylophilus, causes serious damage. Traditional visual detection of nematode infestations is based on characteristic symptoms and depends on expert knowledge, and is, therefore, subject to human bias. Remote sensing methods can provide accurate detection of nematode infested plants and overcome several shortcomings of visual detection by eliminating the need to individually check every plant and manually uproot those plants. Furthermore, by utilizing spectral information outside the visible light spectrum, presymptomatic detection becomes possible. Research on the remote sensing of nematode infestations began in the 1960s, and since then, a large amount of information has been gathered using various sensors, platforms, and analysis methods. Here, several areas of research have been identified that need further efforts in the future, before remote sensing can become a widely used method for noninvasive detection of plant parasitic nematodes.