Identification of asymptomatic plants infected with Citrus tristeza virus from a time series of leaf spectral characteristics

Afonso, Andreia M.; Guerra, Rui; Cavaco, Ana M.; Pinto, Patrícia I. S.; Andrade, André R.; Duarte, Amílcar; Marques, Natália

doi:10.1016/j.compag.2017.08.001

Cited by 18 publications

(12 citation statements)

References 37 publications

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“…Dimension reduction provides a means to recognize patterns in multivariate data sets by constructing weighted combinations of the variables which are able to explain a major portion of the variance ( Henson and Roberts, 2006 ; De Ron et al, 2016 ; Popović et al, 2016 ; Ranjit et al, 2016 ; Afonso et al, 2017 ). Three components/factors were extracted using the Kaiser criterion [eigenvalue (λ) > 1] for the dependent variables set for the fruits ( Figures 5 , 6 , Supplementary Figure S11 , and Table S2 ).…”

Section: Resultsmentioning

confidence: 99%

Abiotic Stress Response to As and As+Si, Composite Reprogramming of Fruit Metabolites in Tomato Cultivars

et al. 2017

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The toxic element arsenic interacts with the beneficial element silicon at many levels of the plant metabolism. The ability of the tomato plant to take up and translocate As into its fruit has risen concerns that it could facilitate the entry of this element into the human food chain above the admitted level. Here, the fruit of two contrasting tomato cultivars, Aragon and Gladis, were evaluated following exposures of either 48 h or 14 days to As-contaminated irrigation water, with or without supplementary Si. The focus was on selected biochemical stress response indicators to dissect metabolic fruit reprogramming induced by As and Si. A multivariate statistical approach was utilized to establish the relationship between tissue As and Si concentrations and selected biochemical aspects of the stress response mechanisms to identify a set of relevant stress response descriptors. This resulted in the recognition of strong cultivar and temporal effects on metabolic and biochemical stress parameters following the treatments. In this paper the metabolic changes in H2O2 content, lipid peroxidation, lycopene and carotenoids content, ascorbate and GSH redox state, total phenolics, ABTS and DPPH radicals inhibition were in favor of an oxidative stress. The significance of some of these parameters as reliable arsenic exposition biomarkers is discussed in the context of the limited knowledge on the As-induced stress response mechanisms at the level of the ripening fruit which presents a distinctive molecular background dissimilar from roots and shoots.

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Section: Resultsmentioning

confidence: 99%

Abiotic Stress Response to As and As+Si, Composite Reprogramming of Fruit Metabolites in Tomato Cultivars

et al. 2017

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“…18S was used as the reference gene to normalize cDNA quantity. The qPCR reaction mixture was previously described . Primer pairs for amplification of the CIN gene were Cin29 Fw 5′‐GATTAGGCAAGTGAAGATG‐3′ and Cin20 Rv 5′‐GTCGTGATGAAACAAATGA‐3′, and for amplification of the control gene 18S, Fw 5′‐GACTACGTCCCTGCCCTTTG‐3′ and Rv 5′‐CGCGATCCGAACATTTCACC‐3′.…”

Section: Methodsmentioning

confidence: 99%

“…A standard curve was prepared for the 1,8‐cineole synthase amplicon and 18S, from purified plasmids containing these sequences, so that the amplification cycle could be related to the initial template quantity, determined using a nanodrop. Copy number determination of the CIN mRNA and 18S was done according to Afonso et al . Relative expression of 1,8‐cineole synthase levels in each plant organ was estimated using the ratio between its copy number and the calculated copy number of the internal control 18S.…”

Section: Methodsmentioning

confidence: 99%

“…The qPCR reaction mixture was previously described. [35] Primer pairs for amplification of the CIN gene were Cin29 Fw 5'-GATTAGG-CAAGTGAAGATG-3' and Cin20 Rv 5'-GTCGTGATGAAA-CAAATGA-3', and for amplification of the control gene 18S, Fw 5'-GACTACGTCCCTGCCCTTTG-3' and Rv 5'-CGCGATCCGAACATTTCACC-3'. All qPCR reactions were performed in duplicate in three independent assays.…”

Section: Real-time Quantitative Pcr (Qpcr)mentioning

confidence: 99%

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Trichome Density in Relation to Volatiles Emission and 1,8‐Cineole Synthase Gene Expression in Thymus albicans Vegetative and Reproductive Organs

Marques

Filipe

Pinto

et al. 2020

Chemistry & Biodiversity

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1,8‐Cineole is the main volatile produced by Thymus albicans Hoffmanns. & Link 1,8‐cineole chemotype. To understand the contribution of distinct plant organs to the high 1,8‐cineole production, trichome morphology and density, as well as emitted volatiles and transcriptional expression of the 1,8‐cineole synthase (CIN) gene were determined separately for T. albicans leaves, bracts, calyx, corolla and inflorescences. Scanning electron microscopy (SEM) and stereoscope microscopy observations showed the highest peltate trichome density in leaves and bracts, significantly distinct from calyx and corolla. T. albicans volatiles were collected by solid phase micro extraction (SPME) and analyzed by gas chromatography‐mass spectrometry (GC/MS) and by GC for component identification and quantification, respectively. Of the 23 components identified, 1,8‐cineole was the dominant volatile (57–93 %) in all T. albicans plant organs. The relative amounts of emitted volatiles clearly separated vegetative from reproductive organs. Gene expression of CIN was assigned to all organs analyzed and was consistent with the relatively high emission of 1,8‐cineole in leaves and bracts. Further studies will be required to analyze monoterpenoid biosynthesis by each type of glandular trichome.

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“…In combination with the fact that some cultivars, most rootstocks, and wild Vitis species may be completely symptomless [12], identifying disease carriers would be a key element in reducing pathogen reservoirs in vineyards and nurseries and especially in rootstock motherblocks. The feasibility of such an approach has already been demonstrated for other phloem-limited pathogens such as citrus tristeza virus or grapevine leafroll-associated viruses [32,49]. Unfortunately, the detection of BN-infected but symptomless plants was not successful under greenhouse conditions, since VNIR and SWIR showed poor classification performances of 68% and 64%, respectively, which is close to a random classifier.…”

Section: Discussionmentioning

confidence: 99%

Detection of Two Different Grapevine Yellows in Vitis vinifera Using Hyperspectral Imaging

et al. 2020

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Grapevine yellows (GY) are serious phytoplasma-caused diseases affecting viticultural areas worldwide. At present, two principal agents of GY are known to infest grapevines in Germany: Bois noir (BN) and Palatinate grapevine yellows (PGY). Disease management is mostly based on prophylactic measures as there are no curative in-field treatments available. In this context, sensor-based disease detection could be a useful tool for winegrowers. Therefore, hyperspectral imaging (400–2500 nm) was applied to identify phytoplasma-infected greenhouse plants and shoots collected in the field. Disease detection models (Radial-Basis Function Network) have successfully been developed for greenhouse plants of two white grapevine varieties infected with BN and PGY. Differentiation of symptomatic and healthy plants was possible reaching satisfying classification accuracies of up to 96%. However, identification of BN-infected but symptomless vines was difficult and needs further investigation. Regarding shoots collected in the field from different red and white varieties, correct classifications of up to 100% could be reached using a Multi-Layer Perceptron Network for analysis. Thus, hyperspectral imaging seems to be a promising approach for the detection of different GY. Moreover, the 10 most important wavelengths were identified for each disease detection approach, many of which could be found between 400 and 700 nm and in the short-wave infrared region (1585, 2135, and 2300 nm). These wavelengths could be used further to develop multispectral systems.

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Identification of asymptomatic plants infected with Citrus tristeza virus from a time series of leaf spectral characteristics

Cited by 18 publications

References 37 publications

Abiotic Stress Response to As and As+Si, Composite Reprogramming of Fruit Metabolites in Tomato Cultivars

Abiotic Stress Response to As and As+Si, Composite Reprogramming of Fruit Metabolites in Tomato Cultivars

Trichome Density in Relation to Volatiles Emission and 1,8‐Cineole Synthase Gene Expression in Thymus albicans Vegetative and Reproductive Organs

Detection of Two Different Grapevine Yellows in Vitis vinifera Using Hyperspectral Imaging

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