Plant disease detection by hyperspectral imaging: from the lab to the field. (1st June 2017)

• Record Type: Journal Article
• Authors: Mahlein, A-K.; Kuska, M. T.; Thomas, S.; Bohnenkamp, D.; Alisaac, E.; Behmann, J.; Wahabzada, M.; Kersting, K.
• Is Part Of: Advances in animal biosciences. Volume 8:Number 2(2017)
• Page Start: 238
• Page End: 243
• Publication Date: 2017-06-01
• Subjects: Plant diseases, -- crop protection, -- resistance, -- hyperspectral imaging, -- machine learning; Animal nutrition -- Periodicals; Animal breeding -- Periodicals; Animal genetics -- Periodicals; Animal biotechnology -- Periodicals; Environmental sciences -- Periodicals; 636.005
• DOI: 10.1017/S2040470017001248
• Languages: English
• ISSNs: 2040-4700

Abstract

Abstract : The detection and identification of plant diseases is a fundamental task in sustainable crop production. An accurate estimate of disease incidence, disease severity and negative effects on yield quality and quantity is important for precision crop production, horticulture, plant breeding or fungicide screening as well as in basic and applied plant research. Particularly hyperspectral imaging of diseased plants offers insight into processes during pathogenesis. By hyperspectral imaging and subsequent data analysis routines, it was possible to realize an early detection, identification and quantification of different relevant plant diseases. Depending on the measuring scale, even subtle processes of defence and resistance mechanism of plants could be evaluated. Within this scope, recent results from studies in barley, wheat and sugar beet and their relevant foliar diseases will be presented.