Early detection of diseases in plant tissue using spectroscopy – applications and limitations

Khaled, Alfadhl Yahya; Aziz, Samsuzana Abd; Bejo, Siti Khairani; Nawi, Nolila Mohd; Seman, Idris Abu; Onwude, Daniel I.

doi:10.1080/05704928.2017.1352510

Cited by 100 publications

(80 citation statements)

References 130 publications

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“…Low-frequency AC passes through the root primarily through the apoplastic (extracellular) pathway, which is almost purely resistive, and only to a lesser extent through the symplastic (intracellular) pathway, which contains capacitive elements, such as cell membranes (Li et al 2017). The electrical properties detected for roots depend on the contribution of these parallel pathways to Ẑ (Repo et al 2000;Khaled et al 2018). Stress-induced changes in root membranes, particularly enhanced lignin and suberin content, modify the ratio of the current pathways, and thus the dielectric response of the roots.…”

Section: Discussionmentioning

confidence: 99%

“…Several technical difficulties limit or restrict the access to root growth and functional parameters in natural soil environments (Milchunas 2012). Therefore, non-intrusive methods, including those based on electrical characterization of the root system in situ, have received increasing attention in recent years (Khaled et al 2018). Significant correlations between the electrical capacitance of the root-substrate system (C R ; Table 1) and the root system size were first found by Chloupek (1972) in various crops.…”

Section: Introductionmentioning

confidence: 99%

“…Environmental stress is reported to cause changes in the electrical properties of plant tissues by modifying numerous features of cell walls, membranes, and the cytosol (Jócsák et al 2010;Khaled et al 2018). For this reason, impedance spectroscopy has become an effective method to study plant responses to, e.g., freeze injury, high salinity, or nutrient stress at the cellular level, using a wide frequency range (Hz-MHz) in isolated tissues and organs (Repo et al 2000;Hamed et al 2016;Li et al 2017).…”

Section: Introductionmentioning

confidence: 99%

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Electrical characterization of the root system: a noninvasive approach to study plant stress responses

et al. 2019

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A pot experiment was designed to demonstrate that the parallel, single-frequency detection of electrical capacitance (C R), impedance phase angle (Φ R), and electrical conductance (G R) in root-substrate systems was an adequate method for monitoring root growth and some aspects of stress response in situ. The wheat cultivars 'Hombar' and 'TC33' were grown in a rhyolite-vermiculite mixture under control, and low, medium, and high alkaline (Na 2 CO 3) conditions with regular measurement of electrical parameters. The photochemical efficiency (F v /F m) and SPAD chlorophyll content were recorded nonintrusively; the green leaf area (GLA), shoot dry mass (SDM), root dry mass (RDM), and root membrane stability index (MSI) were determined after harvest. C R progressively decreased with increasing alkalinity due to impeded root growth. Strong linear C R-RDM relationships (R 2 = 0.883-0.940) were obtained for the cultivars. Stress reduced |Φ R |, presumably due to the altered membrane properties and anatomy of the roots, including primarily enhanced lignification. G R was not reduced by alkalinity, implying the increasing symplastic conductivity caused by the higher electrolyte leakage indicated by decreasing root MSI. F v /F m , SPAD value, GLA, and SDM showed decreasing trends with increasing alkalinity. Cultivar 'TC33' was comparatively sensitive to high alkalinity, as shown by the greater relative decrease in C R , SDM, and RDM under stress, and by the significantly lower MSI and higher (moderately reduced) |Φ R | compared to the values obtained for 'Hombar'. Electrical root characterization proved to be an efficient non-intrusive technique for studying root growth and stress responses, and for assessing plant stress tolerance in pot experiments.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Electrical characterization of the root system: a noninvasive approach to study plant stress responses

et al. 2019

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“…Ozone damage is predicted to become an increasing threat to global food production due to climate change (3,4). At present, late-stage visual identification (5,6) of necrotized leaf tissue, followed by off-site laboratory confirmation of reactive oxygen species in digested samples, is the predominant method of recording ozone damage in crops (7,8). However, visual observation cannot reveal early-stage ozone damage, and many commonplace abiotic stressors, such as drought, could also result in necrotized leaf tissue, preventing on-time interventions (7,9).…”

Section: Introductionmentioning

confidence: 99%

On-site identification of ozone damage in fruiting plants using vapor-deposited conducting polymer tattoos

et al. 2020

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Climate change is leading to increased concentrations of ground-level ozone in farms and orchards. Persistent ozone exposure causes irreversible oxidative damage to plants and reduces crop yield, threatening food supply chains. Here, we show that vapor-deposited conducting polymer tattoos on plant leaves can be used to perform on-site impedance analysis, which accurately reveals ozone damage, even at low exposure levels. Oxidative damage produces a unique change in the high-frequency (>104 Hz) impedance and phase signals of leaves, which is not replicated by other abiotic stressors, such as drought. The polymer tattoos are resilient against ozone-induced chemical degradation and persist on the leaves of fruiting plants, thus allowing for frequent and long-term monitoring of cellular ozone damage in economically important crops, such as grapes and apples.

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“…Various machine learning methods such as Support Vector Machines (SVM) [10], k-Nearest neighbor (k-NN), Naive Bayes, or Random Forest [19] are applied. For instance, Spectroscopy of plant tissues is used in [26]. In other study [14], multispectral data are used as features for Neural Networks to detect diseases on cucumber.…”

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confidence: 99%

Plant diseases detection with low resolution data using nested skip connections

et al. 2020

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Natural disasters, climate change[54] and plant diseases[51] are among many factors that threaten the food security. Plant diseases in particular, may cause great loss not only for farmers, but also for global economy. For instance, The International Potato Center (CIP) reports that around 15 % loss of potatoes production[24] is due to late blight diseases only. Globally, plant diseases cause more than 20 % crop loss annually[49]. The

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Early detection of diseases in plant tissue using spectroscopy – applications and limitations

Cited by 100 publications

References 130 publications

Electrical characterization of the root system: a noninvasive approach to study plant stress responses

Electrical characterization of the root system: a noninvasive approach to study plant stress responses

On-site identification of ozone damage in fruiting plants using vapor-deposited conducting polymer tattoos

Plant diseases detection with low resolution data using nested skip connections

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