Hyperspectral remote sensing of grapevine drought stress

Abstract

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Morphophysiology of Potato (Solanum tuberosum) in Response to Drought Stress: Paving the Way Forward

“…Thus, screening for drought tolerant cultivars by observing the canopy architecture of potato under drought stress will likely be faster, more convenient, and higher resolution than the less sensitive, delicate, and labor-intensive process of measuring root growth ( Zarzyńska et al, 2017 ). However, unlike in other crops ( Susič et al, 2018 ; Asaari et al, 2019 ; Zovko et al, 2019 ), very little work has been conducted with potato that utilizes modern phenotyping methods, such as multispectral, hyperspectral or three-dimensional imaging. These technologies present an opportunity to better understand the effects of drought stress on potato and will be a useful to accelerate the screening of drought tolerant cultivars.…”

“…There have been recent studies, published in the last five years, observing the effects of drought on the morphophysiology of potato ( Aliche et al, 2018 ; Chang et al, 2018 ; Michel et al, 2019 ; Pourasadollahi et al, 2019 ), but such studies are limited in the scientific literature. Unlike in other crops, including tomato ( Susič et al, 2018 ), grape ( Zovko et al, 2019 ), and maize ( Asaari et al, 2019 ), there has been even less research investigating the effects of drought on potato using modern phenotyping methods, such as multispectral, hyperspectral or three-dimensional imaging. In a review published in 2013 regarding drought tolerance in potato, the mean year of publication for citations that demonstrated the measurement of drought-related phenotypic responses in potato was 2001 ( Monneveux et al, 2013 ).…”

Proximal Methods for Plant Stress Detection Using Optical Sensors and Machine Learning

“…Rather than collecting spectra from an entire image or an entire plant leaf, where spectra from the stressed and unaffected areas are mixed together, hyperspectral imaging can provide more sophisticated data that can isolate spectra only from the affected area and identify specific imaging patterns and characteristics. This method has become increasingly popular for plant phenotyping and stress detection in agriculture [29][30][31] and has been used to identify plant responses to both abiotic and biotic stresses, such as drought stress in maize [32] and barley [33], yellow rust [34] and powdery mildew [35] in wheat, salt stress in okra [36], and Black Sigatoka disease in banana plants [37].…”

Plant pests and disease detection using optical sensors / Daljinsko zaznavanje rastlinskih bolezni in škodljivcev

“…High spectral resolutions enable not only detection of abiotic and biotic stress, but also chemometric analyses, and identification of wavelengths related to infections and infestations, as well as early (i.e. presymptomatic) detection of infections or infestations (Susič et al 2018, Zovko et al 2019. Hyperspectral remote sensing has been used to quantify Rhizoctonia crown and root rot in sugar beet (Reynolds et al 2012), Venturia inaequalis infections in apple (Delialieux et al 2007), Phytophthora infestans in tomato (Wang et al 2008), combined infections of Rhizoctonia and cyst nematodes (H. schachtii) in sugar beet (Hillnhütter et al 2011), Fusarium head blight in wheat (Bauriegel et al 2011), and differentiation between drought and biotic stress combined with presymptomatic detection of root-knot nematode (Meloidogyne incognita) infestations in tomato plants (Susič et al 2018).…”