scholarly journals Non-Destructive Early Detection and Quantitative Severity Stage Classification of Tomato Chlorosis Virus (ToCV) Infection in Young Tomato Plants Using Vis–NIR Spectroscopy

2020 ◽  
Vol 12 (12) ◽  
pp. 1920
Author(s):  
Antonios Morellos ◽  
Georgios Tziotzios ◽  
Chrysoula Orfanidou ◽  
Xanthoula Eirini Pantazi ◽  
Christos Sarantaris ◽  
...  
Keyword(s):  
Vegetation Indices ◽  
Nir Spectroscopy ◽  
Spectral Measurements ◽  
Laboratory Methods ◽  
Tomato Production ◽  
Tomato Plants ◽  
Tomato Chlorosis Virus ◽  
Tomato Pathogen ◽  
Non Destructive

Tomato chlorosis virus (ToCV) is a serious, emerging tomato pathogen that has a significant impact on the quality and quantity of tomato production worldwide. Detecting ToCV via means of spectral measurements in an early pre-symptomatic stage offers an alternative to the existing laboratory methods, leading to better disease management in the field. In this study, leaf spectra from healthy and diseased leaves were measured with a spectrometer. The diseased leaves were subjected to RT-qPCR for the detection and quantification of the titer of ToCV. Neighborhood component analysis (NCA) algorithm was employed for the feature selection of the effective wavelengths and the most important vegetation indices out of the 24 that were tested. Two machine learning methods, namely XY-fusion network (XY-F) and multilayer perceptron with automated relevance determination (MLP–ARD), were employed for the estimation of the disease existence and viral load in the tomato leaves. The results showed that before outlier elimination, the MLP–ARD classifier generally outperformed the XY-F network with an overall accuracy of 92.1% against 88.3% for the XY-F. Outlier elimination contributed to the performance of the classifiers as the overall accuracy for both XY-F and MLP–ARD reached 100%.

scholarly journals Feasibility of Using VIS/NIR Spectroscopy and Multivariate Analysis for Pesticide Residue Detection in Tomatoes

Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 196
Author(s):  
Araz Soltani Nazarloo ◽  
Vali Rasooli Sharabiani ◽  
Yousef Abbaspour Gilandeh ◽  
Ebrahim Taghinezhad ◽  
Mariusz Szymanek ◽  
...  
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Low Cost ◽  
Moving Average ◽  
Nir Spectroscopy ◽  
Control Treatment ◽  
Residue Detection ◽  
Non Destructive ◽  
Reflective Spectroscopy

The purpose of this work was to investigate the detection of the pesticide residual (profenofos) in tomatoes by using visible/near-infrared spectroscopy. Therefore, the experiments were performed on 180 tomato samples with different percentages of profenofos pesticide (higher and lower values than the maximum residual limit (MRL)) as compared to the control (no pesticide). VIS/near infrared (NIR) spectral data from pesticide solution and non-pesticide tomato samples (used as control treatment) impregnated with different concentrations of pesticide in the range of 400 to 1050 nm were recorded by a spectrometer. For classification of tomatoes with pesticide content at lower and higher levels of MRL as healthy and unhealthy samples, we used different spectral pre-processing methods with partial least squares discriminant analysis (PLS-DA) models. The Smoothing Moving Average pre-processing method with the standard error of cross validation (SECV) = 4.2767 was selected as the best model for this study. In addition, in the calibration and prediction sets, the percentages of total correctly classified samples were 90 and 91.66%, respectively. Therefore, it can be concluded that reflective spectroscopy (VIS/NIR) can be used as a non-destructive, low-cost, and rapid technique to control the health of tomatoes impregnated with profenofos pesticide.

scholarly journals Responses of Tomatoes Grafting Using Variation of Rootstock against Virus Infection and Tomato Yields

2020 ◽  
Vol 24 (1) ◽  
pp. 98
Author(s):  
Tri Retno Widyastuti ◽  
Sri Sulandari ◽  
Sedyo Hartono ◽  
Triwidodo Arwiyanto
Keyword(s):  
Viral Infection ◽  
Viral Infections ◽  
Field Research ◽  
Viral Diseases ◽  
Specific Primer ◽  
Resistance Response ◽  
Tomato Production ◽  
Tomato Plants ◽  
Randomized Design ◽  
Tomato Chlorosis Virus

Grafting methods on tomato have been done to reduce the infection rate of various pathogens. Begomovirus and Crinivirus are important viruses in tomato plants. The research aimed to determine the resistance response of tomato plants to viral infection, and tomato production. Field research was conducted in Harjobinangun, Pakem, Sleman, Yogyakarta in the endemic area of the viral diseases transmitted by Bemisia tabaci. This experiment used a Completely Randomized Design non-factorial with “Servo” as scion and “Amelia”, “H-7996”, “Mawar” as rootstock. The disease development, presence of viral diseases, and tomato yields were observed. PCR detection using Krusty & Hommr primer successfully amplified Begomovirus DNA bands with an approximate size of 580 bp in tomato plant with interveinal chlorosis, curling, thick, rigid, and stunt symptoms. Chlorotic spots and yellowing symptoms successfully amplified using ToCV-CF/ToCV-CR specific primer for the amplification of Tomato chlorosis virus with DNA band approximately size of 360 bp, whereas using TICV-CF/TICV-CR specific primer could not amplify the virus cDNA. The leaves roll upward with purple interveinal symptoms that were not infected by both viruses. Both viral infections affected the quality of the fruit which indicated by a higher number of abnormal fruits. “Servo” grafted onto “Amelia” and non-grafted Servo were tolerant to viral infection, “Servo” grafted onto “H-7996” or to “Mawar variety were susceptible to viral infection, self-grafted Servo were very susceptible to viral infection. 

scholarly journals Molecular Characterization and Detection of a Genetically Distinct Tomato Chlorosis Virus Strain in Taiwan

Plant Disease ◽  
2018 ◽  
Vol 102 (3) ◽  
pp. 600-607 ◽  
Author(s):  
Ya-Chi Kang ◽  
Yun-Chi Wang ◽  
Chun-Ming Hsia ◽  
Wen-Shi Tsai ◽  
Li-Hsin Huang ◽  
...  
Keyword(s):  
Genomic Sequence ◽  
Phylogenetic Analyses ◽  
Whole Genome Sequence ◽  
Rt Pcr ◽  
Degenerate Primers ◽  
Tomato Production ◽  
Tomato Plants ◽  
Infected Tomato ◽  
Tomato Chlorosis Virus ◽  
Central Taiwan

The whitefly-transmitted tomato chlorosis virus (ToCV) belonging to the genus Crinivirus (family Closteroviridae) affects tomato production worldwide. ToCV was first recorded in Taiwan in 1998 affecting tomato production. In this study, a local virus isolate XS was obtained, after serial whitefly transmissions from a diseased tomato plant displaying general chlorosis were collected in central Taiwan. The whole genome sequence of XS was determined from cDNA fragments amplified by reverse transcription (RT)-PCR, first using the degenerate primers for viruses of Closteroviridae and followed by degenerate and specific primers designed on available sequences of the ToCV isolates. The nucleotide (nt) sequences of RNA-1 and RNA-2 of the XS shared low identities of 77.8 to 78% and 78 to 78.1%, respectively, with genome segments of other ToCV isolates. Nevertheless, the viral RNA-dependent RNA polymerase (RdRp), heat shock protein 70 homolog (Hsp70h), and major capsid protein (CP) shared 88.3 to 96.2% amino acid (aa) identities with other ToCV isolates, indicating that XS is a new strain of this virus. Phylogenetic analyses of these three proteins indicated that all ToCV isolates from different counties outside Taiwan are closely related and clustered in the same clade, whereas the XS isolate is distinct and forms a unique branch. A one tube RT-PCR assay using primers designed from the genomic sequence of the XS was able to detect the ToCV-XS in infected tomato plants and in individual whiteflies. A field survey during 2013 to 2016 revealed a high ToCV-XS prevalence of 60.5% in 172 tested tomato samples, demonstrating that ToCV-XS is becoming an emerging threat for tomato production in Taiwan.

Use of linguistic estimates and vegetation indices to assess post-fire vegetation regrowth in woodland areas

2010 ◽  
Vol 19 (1) ◽  
pp. 94 ◽  
Author(s):  
Carol R. Jacobson
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Moisture Index ◽  
Index Data ◽  
Subset Regression ◽  
Simple Ratio ◽  
The Relationship ◽  
Non Destructive

This study examined an area of woodland that was recovering from severe fire in Royal National Park (NSW, Australia). A non-destructive method of field sampling is required for vulnerable recovering vegetation and therefore classification of digital photographs using linguistic terms was trialled. The linguistic data for three vegetation strata (canopy, shrub and ground) were converted to crisp scores and compared with vegetation index data derived from remotely sensed imagery. All possible subset regression was used to test the proposition that the combined vegetation scores (independent variables) would explain the values of NDVI (Normalized Difference Vegetation Index) and NDMI (Normalized Difference Moisture Index). Vegetation scores for the three strata were also combined using simplified weighting ratios to assess broad relationships between the indices and field data. The combined vegetation scores explained ~60% of the variation in the vegetation index data and inclusion of variables representing multiple strata explained more of the variation than any single variable. The precise value of the weights used to combine the layers did not affect the strength of the association. A simple ratio is proposed that may be useful to estimate woodland parameters under similar conditions, by inversion of the relationship with vegetation index data.

scholarly journals Physalis angulata: A New Natural Host of Tomato chlorosis virus in Brazil

Plant Disease ◽  
2013 ◽  
Vol 97 (5) ◽  
pp. 692-692 ◽  
Author(s):  
M. E. N. Fonseca ◽  
L. S. Boiteux ◽  
H. Abreu ◽  
I. Nogueira ◽  
R. C. Pereira-Carvalho
Keyword(s):  
Magnesium Deficiency ◽  
Natural Host ◽  
Tomato Production ◽  
Tomato Plants ◽  
Field Samples ◽  
High Incidence ◽  
Physalis Angulata ◽  
Tomato Chlorosis Virus ◽  
Biotype B ◽  
Specific Amplicon

Tomato chlorosis virus (ToCV) and Tomato infectious chlorosis virus (TICV) are the two Solanaceae-infecting Crinivirus species (family Closteroviridae) of worldwide importance. In Brazil, only ToCV has been detected under natural conditions infecting tomato (Solanum lycopersicum), sweet pepper (Capsicum annuum), and potato (S. tuberosum), causing foliar chlorosis (1, 3). However, there are no formal reports of alternative weed hosts of ToCV. During crop surveys in Capão Bonito, São Paulo State, Brazil (May 2011), a high incidence (above 20%) of plants of the weed, cut leaf ground cherry (Physalis angulata L.) growing around and within a tomato (cv. Alambra) field with a high incidence of ToCV, were found displaying interveinal chlorosis on the lower leaves, similar to those induced by magnesium deficiency. The P. angulata plants also had high populations of whiteflies (Bemisia tabaci biotype B). Ten leaf samples were taken from individual symptomatic ground cherry and tomato plants for Crinivirus testing. Total nucleic acids were extracted from 2 g of symptomatic and healthy leaf tissues of both hosts using Whatman CF-11 cellulose (Sigma) as described (4). The purified double stranded RNA samples were used as a template in reverse transcription (RT)-PCR using specific primers targeting the p22 gene region in the genome of ToCV (2). Only the 566-bp ToCV-specific amplicon was detected in all field samples. Sequences of samples from the P. angulata and tomato cDNA amplicons were identical to each other (GenBank Accession No. JX187514) and they showed 99% identity with the ToCV RNA 1 from a tomato isolate from Florida (AY903447). This confirmed the initial hypothesis of Crinivirus infection. Cuttings of symptomatic P. angulata plants were also obtained and kept in a voile cage under greenhouse conditions together with healthy seedlings of P. angulata and the begomovirus-resistant inbred tomato line ‘TX-468RG.’ Fifty aviruliferous B. tabaci (biotype B) adults were placed in the cage. Similar symptoms were observed 50 days after exposure to whiteflies in both hosts. Transmission to P. angulata and to ‘TX-468RG’ was also confirmed via sequencing of ToCV-specific amplicon, demonstrating the infectivity of the isolate to both hosts. To our knowledge, this is the first report of P. angulata as a natural host of ToCV in Brazil. This weed is often present in the commercial fields because of its natural tolerance to herbicides currently used in tomato production. The ToCV-infected P. angulata plants might serve as alternative sources of inoculum for the surrounding tomato fields. The environmental persistence of P. angulata combined with its intense whitefly colonization might allow a year-round ToCV exposure for tomato plants under field conditions in this major production area of Brazil where at least 25 million tomato plants are cultivated annually. References: (1) J. C. Barbosa et al. Trop. Plant Pathol. 36: 256, 2011. (2) M. I. Font et al. Plant Dis. 86:696, 2002. (3) D. M. S. Freitas et al. Plant Dis. 96:593, 2012. (4) R. A. Valverde et al. Plant Dis. 74:285, 1990.

Identification prediction moisture content of Thai coconut sugar (Cocos nucifera L.) using FT-NIR spectroscopy

Food Research ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 382-385
Author(s):  
D. Thumrongchote
Keyword(s):  
Moisture Content ◽  
Cocos Nucifera ◽  
Nir Spectroscopy ◽  
Grocery Stores ◽  
Absorbance Spectrum ◽  
Coconut Tree ◽  
Cocos Nucifera L ◽  
The Cost ◽  
Non Destructive ◽  
Low Glycemic Index

Coconut sugar is a local sugar from the blossoms of a coconut tree. It has been considered a healthy sugar due to its low glycemic index. There is an attempt to add other sugar to it to lower the cost. Thus, this research aimed to identify Thai coconut sugar and to establish models for predicting the moisture content of coconut sugar by using FT-NIR spectroscopy. Thai coconut sugar samples were purchased from local grocery stores in four provinces, online, and the community market. Their moisture contents were varied and equilibrated for 24 hrs prior to the measurements of moisture and FT-NIR spectra. The results showed that FT-NIR spectra of Thai coconut sugar differ from sucrose, glucose and fructose at the absorbance spectrum of 5379-5011 cm-1 . FT-NIR spectroscopy of 54 known moisture samples of Thai coconut sugar was used to obtain a model to predict moisture content. The predicted equation, using the PLS technique with the Spectrum Quant program, was found to give a standard error of prediction (SEP) 0.077% (less than 0.10%), indicating a non-destructive method of accurately and precisely predicting moisture levels in the coconut sugar. The results obtained suggested that FTNIR spectroscopy has the potential to be used as a tool to identify Thai coconut sugar accurately. It can rapidly predict the moisture content in the sample which will be useful in quality control standards.

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