Hyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stress

This review explores how imaging techniques are being developed with a focus on deployment for crop monitoring methods. Imaging applications are discussed in relation to both field and glasshouse-based plants, and techniques are sectioned into ‘healthy and diseased plant classification’ with an emphasis on classification accuracy, early detection of stress, and disease severity. A central focus of the review is the use of hyperspectral imaging and how this is being utilised to find additional information about plant health, and the ability to predict onset of disease. A summary of techniques used to detect biotic and abiotic stress in plants is presented, including the level of accuracy associated with each method

Rapid Fusarium head blight detection on winter wheat ears using chlorophyll fluorescence imaging

Fusarium infection on wheat is a widespread thread for humans' and animals' nutrition as these fungi are known to produce the highly dangerous mycotoxin deoxynivaleol (DON). Besides this, Fusarium also induces head blight, a disease resulting in huge economic losses due to shrivelled and low mass or dead kerneIs. Early disease detection could help to reduce yield losses and health threads from DON contamination. The potential of chlorophyll fluorescence imaging (CFI) to yield these aims was investigated in laboratory experiments applying a FluorCam 700MF commercial CFI system. Healthy (control) plants as well as plants artificially infected with Fusarium culmorum were rated visually according to the stage of development and the degree of disease. Subsequently, a chlorophyll fluorescence image analysis of the potential maximum photochemical efficiency (Fv/Fm) was applied to determine the degree and the distribution of the damage of the ears. Between the sixth and eleventh day after artificial inoculation photosynthetic activity of single damaged kernels of diseased ears dropped to zero.Although this only marginally affected the average maximum photochemical efficiency of entire ears, the infection led to a significant increase in the statistical distribution of Fv/Fm in the images. Pixelwise integration of Fv/Fm-values (from low to high) of the fluorescence images allowed a differentiation, in steps of 10%, between ears of different degree of disease of 10% on in the BBCH stage 75. Lowest level of disease detection by CFI corresponded to a visually rated degree of disease of at least 5%. However, the possibility to distinguish between diseased and healthy ears became highly limited with incipient ripening of kerneIs and concomitant chlorophyll degradation at growth stage 81.Abbreviations: CFI - chlorophyll fluorescence imaging, dai - days after inoculation, DON - deoxynivalenol, Fo - basic fluorescence emission of a dark-adapted plant, Fm - maximal fluorescence emission of a dark-adapted plant, Fv = Fm - Fo - variable fluorescence measured on dark-adapted plant, Fv/Fm - maximum fluorescence yield of PS II (photosynthetic efficiency), PS II - Photosystem I

The Characteristic of Hyperspectral Image of Wheat Seeds during Sprouting

International audienceThe pre-harvest sprouting of wheat have significant influence for its quality and yield, therefore the fast detection of sprouting extent of wheat is very important for breeding and producing. In this study, the hyperspectral images of these seeds were collected by a near infrared hyperspectral imaging system, the wavelength of which was 850-1700 nm after wheat germination experiment at 0h, 12h, 24h, and 48h. The original light intensity of embryo and endosperm were extracted, and were then changed to reflectivity for later analysis. The image and spectral information of wheat with different parts, different varieties and different sprouting extent were compared. The results showed that after 12h sprouting, the reflectivity of embryo was lower than that of endosperm for the same seed, this is mainly due to the water and fat content of embryo was higher than the endosperm portions. For the same varieties of wheat seed at the germination of 12h, 24h and 48h,in the wavelength range of 870-1300 nm, the reflectivity increased with the increase of sprouting time, it was related to the changes of its internal content of fat in the seed germination process. At 1400nm, the reflectivity of sprouted wheat seeds were all lower than that of dry seeds, it was related to the rise of internal water content in the process of seed germination. Due to differences in seed water absorption and sprouting résistance, for different varieties of wheat seeds, its spectral characteristics are also different. The presented indicated that hyperspectral imaging could reflect the characteristics of sprouted wheat seeds, which provide some basis for explore the sprouting index by hyperspectral imaging

MALDI-TOF MS to identify the pineapple pathogen Fusarium guttiforme and its antagonist Trichoderma asperellum on decayed pineapple

Matrix-assisted laser desorption⁄ionisation time-of flight mass spectrometry (MALDI-TOF MS) has been used to identify some Fusarium and Trichoderma species, but early detection of fungal diseases by this technique has not yet been fully addressed. In this study, MALDI-TOF MS was tested to identify F. guttiforme on pineapple side shoots in situ. The efficacy of filamentous fungi for controlling fungal diseases is well documented. However, there is uncertainty whether the biocontrol agent is out growing the pathogen sufficiently to be identified. In this paper, a multistep identification of a plant pathogen (F. guttiforme) and its antagonist (T. asperellum) using MALDI-TOF MS is demonstrated.Brazilian Collection of Environmental and Industrial Microorganisms/University of Campinas (CBMAI, Brazil) for Trichoderma isolates and to Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, Brazil), and Fundação de Amparo à Pesquisa do Estado do Espírito Santo (FAPES, ES, Brazil) for the funding received