Application of thermal and visible imaging to estimate stripe rust disease severity in wheat using supervised image classification methods

Reliable and accurate estimation of plant disease severity at the field scale is a key factor for predicting yield losses, disease management and food security. A field experiment was designed and conducted during 2017–18 and 2018–19 with 24 wheat cultivars to estimate the stripe rust severity by supervised classification of thermal and visible images using parallelepiped, minimum distance, mahalanobis distance, maximum likelihood, support vector machine and neural network methods of image classification. Results demonstrated the potential of thermal and visible imaging techniques to estimate wheat stripe rust severity with good accuracy. For both visible and thermal images used in this study, support vector machine gave the best estimates of the rust severity, while the parallelepiped method was the worst-performing method. Support vector machine and neural network methods showed d-index, Nash-Sutcliffe efficiency and coefficient of determination values above 85%, with accuracies above 98% and kappa coefficient above 0.97 for both thermal and visible images. Comparison of thermal and visible image classification performance revealed that for all the methods except support vector machine, the estimated rust severity, overall accuracy and kappa coefficient of thermal images were better than visible images. The present study clearly showed that both thermal and visible image analysis can be applied as a rapid non-destructive technique to estimate the wheat rust severity under field conditions. The study also provided a comparative insight into thermal and visible image classification methods that have great potential for sustainable plant disease management in modern agriculture.     

Effect of mustard green manure and dried plant residue on chickpea wilt (Fusarium oxysporum f.sp. ciceris)

Pot experiments were carried out in the green house at Amhara Regional Agriculture Research Institute (ARARI) Bahirdar, Ethiopia, to evaluate the potential of Brassica carinata cultivars, namely Holleta-l, S-67 and Yellow Dodola in 2007 and 2008. The effect of B. carinata (Ethiopian mustard) cultivars Holleta-1, S-67 and Yellow Dodola as green manure and Holleta-1 as dried plant residue on chickpea fusarium wilt (Fusarium oxysporum f.sp. ciceris) was studied. Six rates of green manure and dried plant residue (0, 20, 40, 60, 80 and 100 g) each per kg of pathogen-infested soil were used in the experiments. Infested soil without B. carinata cultivars amendment as a control and susceptible check variety JG-62 without amendment was used in the experiments. In the experiments, the treatments were arranged in randomised complete block design in three replications and repeated twice. Data on seedling emergence, wilt incidence, fresh weight and dry weight were collected. The amendments of infested soil with B. carinata cultivars green manure and dried plant residue reduced the incidence of chickpea fusarium wilt. The incorporation of the green manure Holleta-1, S-67 and Yellow Dodola at 20–100 g/kg of infested soil was effective in reducing wilt incidences on chickpea. However, the incorporation of Yellow Dodola at 80 and 100 g green manure per kg of infested soil were the best combination in reducing significantly wilt incidence. The application of the dried plant residue at 20–100 g/kg of infested soil was effective in reducing wilt incidences on chickpea. However when applied dried plant residue at 60, 80 and 100 g green manure per kg of infested soil were better in reducing wilt incidence as compared to 20 and 40 g/kg of infested soil. The three cultivars green manure incorporated at different level of doses affected the influence of fusarium wilt on the fresh and dry weight respectively. The use of Holleta-1 green manure at 20–100 g/kg of infested soil significantly reduced disease incidence in the range of 20.0–33.3%. Green manure amendment S-67 significantly reduced disease incidence in the range of 20.0–46.6%. Yellow Dodola reduce disease incidence with 26.7–60%. The dried plant residue incorporated at different level influence fusarium wilt. The application of Holleta-1 dried plant residue at 20–100 g/kg of infested soil reduced disease incidence in the range 20.0–26.7%. The results imply the potential of using B. carinata green manure and dried plant residue as cultural management components in chickpea fusarium wilt disease management.     

Evaluation of Streptomyces spp. and Bacillus spp. for biocontrol of Fusarium wilt in chickpea (Cicer arietinum L.)

A study was carried out to test direct and indirect antagonistic effect against Fusarium wilt, caused by Fusarium oxysporum f. sp. ciceri (FOC), and plant growth-promoting (PGP) traits of bacteria isolated from rhizosphere soils of chickpea (Cicer arietinum L.). A total of 40 bacterial isolates were tested for their antagonistic activity against FOC and of which 10 were found to have strong antagonistic potential. These were found to be Streptomyces spp. (five isolates) and Bacillus spp. (five isolates) in the morphological and biochemical characterisation and 16S rDNA analysis. Under both greenhouse and wilt sick field conditions, the selected Streptomyces and Bacillus isolates reduced disease incidence and delayed expression of symptoms of disease, over the non-inoculated control. The PGP ability of the isolates such as nodule number, nodule weight, shoot weight, root weight, grain yield and stover yield were also demonstrated under greenhouse and field conditions over the non-inoculated control. Among the ten isolates, Streptomyces sp. AC-19 and Bacillus sp. BS-20 were found to have more potential for biocontrol of FOC and PGP in chickpea. This investigation indicates that the selected Streptomyces and Bacillus isolates have the potential to control Fusarium wilt disease and to promote plant growth in chickpea.     

Effect of Brassica carinata (L.) biofumigants (seed meal) on chickpea wilt (Fusarium oxysporum f.sp. ciceris), growth,yield and yield component in Ethiopia

Pot experiments were carried out in the green house at Amhara Regional Agriculture Research Institute (ARARI) Bahirdar, Ethiopia to evaluate the potential of Brassica carinata cultivars namely; Holleta-l, S-67 and Yellow Dodola in 2007 and 2008. The treatment effects of B. carinata (L.) cultivars Holleta–1, S-67 and Yellow Dodola seed meals on chickpea fusarium wilt (Fusarium oxysporum f.sp. ciceris) were studied. Six rates of seed (0, 5, 10, 15, 20 and 25 g/kg of infested soil) were used. Infested soil without B.carinata cultivars amendments as a control and susceptible check variety JG-62 also without amendments were used in all the experiments. For each seed meal experiment, the treatments were arranged in factorial randomised complete block design in three replications. Data on seedling emergence, wilt incidence, fresh weight, dry weight, pod per plant, seed per pod, hundred seed weight and yield per hectare were collected. The amendments of infested soil with B.carinata cultivars seed meal reduced the incidence of chickpea fusarium wilt and increased yield per hectare. The interaction of the seed meal Holleta-1, S-67 and Yellow Dodola at 10–25 g/kg infested soil were effective in reducing wilt incidences on chickpea. However, the interaction of Yellow Dodola with 20 and 25 g seed meal per kg infested soil were the best combination in reducing significantly wilt incidence. The three cultivars incorporated at different level of doses significantly affected the influence of Fusarium wilt on the fresh weight, dry weight, pod per plant, seed per pod, hundred seed weight and yield per hectare. The highest yield kg/ha was recorded in combination of Yellow Dodola seed meal at 20 and 25 g followed by S-67 and Holleta-1 at 25 g /kg infested soil, respectively. The interaction of Holleta-1 at 5–25 infested soil significantly reduced disease incidence up to 16.7–43.3% and increased yield per hectare with mean by (30%) over the control. Seed meal amendment S-67 significantly reduce disease incidence 26.7–46.7% and increased yield kg/ha with mean by (36.7%) from the unamended control. Yellow dodola reduces disease incidence with 26.7–63.3% and increased yield kg/ha with mean by (45%) from the unamended control. The result indicates the potential of using Brassica crop seed meal amendment as useful component of integrated chickpea wilt management.     

Effect of genotype and root colonization in biological control of fusarium wilts in pigeonpea and chickpea by Pseudomonas aeruginosa PNA1

Pseudomonas aeruginosa PNA1, an isolate from chickpea rhizosphere in India, protected pigeonpea and chickpea plants from fusarium wilt disease, which is caused by Fusarium oxysporum f.sp. ciceris and Fusarium udum. Inoculation with strain PNA1 significantly reduced the incidence of fusarium wilt in pigeonpea and chickpea on both susceptible and moderately tolerant genotypes. However, strain PNA1 protected the plants from fusarium wilt until maturity only in moderately tolerant genotypes of pigeonpea and chickpea. Root colonization of pigeonpea and chickpea, which was measured using a lacZ-marked strain of PNA1, showed tenfold lower root colonization of susceptible genotypes than that of moderately tolerant genotypes, indicating that this plant-bacteria interaction could be important for disease suppression in this plant. Strain PNA1 produced two phenazine antibiotics, phenazine-1-carboxylic acid and oxychlororaphin, in vitro. Its Tn5 mutants (FM29 and FM13), which were deficient in phenazine production, caused a reduction or loss of wilt disease suppression in vivo. Hence, phenazine production by PNA1 also contributed to the biocontrol of fusarium wilt diseases in pigeonpea and chickpea.     

Induction of systemic resistance in chickpea against Fusarium wilt by Bacillus strains

Plant growth promoting rhizobacteria (PGPR) strains Rb29 (B. amyloliquefaciens MF352007), Bs1 (B. subtilis MF352017) and Bt1 (B. tequilensis MF352019) were tested for growth promotion and for their ability to induce systemic resistance against Fusarium wilt, a vascular disease of chickpea, using two methods that include whole plant and a split-root system. Bacillus strains and Fusarium oxysporum f. sp. ciceris (FOC) were inoculated on separate halves of roots of chickpea seedlings at the same time and then planted in separate pots either in superposition or one side of the other. All Bacillus strains systemically induced resistance against FOC, and significantly (p < 0.05) reduced the wilt disease by 98–100%. Application of Bacillus strains effectively enhanced plant growth, leading to increased plant height, root length, a fresh and dry weight of shoots and roots. These results help to explain the role of strains of Bacillus in growth promotion and biological control of Fusarium wilt in chickpea. This is the first report of systemic-induced resistance against Fusarium wilt in chickpea obtained by application of Bacillus strains to a root system spatially separated from the FOC-inoculated root.     

Field evaluation of eco-friendly biocontrol package for the management of pod borer,Helicoverpa armigera Hubner,and fusarium wilt in chickpea,Cicer arietinum

Helicoverpa armigera is a serious pest of chickpea and causes great damage to crop. Extensive and indiscriminate use of insecticides has led to the development of resistance in H. armigera. Among the several alternative methods for management of H. armigera, the nuclear polyhedrosis virus (NPV) is promising, whereas Trichoderma sp. have shown promising results against chickpea wilt. The experiments to evaluate biocontrol package against H. armigera and wilt disease under field conditions were conducted. Lowest H. armigera larval population (0.71 larvae/plant) was recorded in chemical control, which was at a par with biocontrol package (0.91 larvae/plant), and both the treatments were significantly better than control. Lowest per cent pod damage (3.85%) was recorded in chemical control followed by biocontrol treatment (5.08%) and unsprayed control (8.61%). The yields from biocontrol package (13.45 q/ha) and chemical control (15.37 q/ha) were significantly higher than unsprayed control (10.7 q/ha). There was no disease incidence in all treatments in both 2008 and 2009.     

Efficacy of Bacillus subtilis and Trichoderma harzianum combination on chickpea Fusarium wilt caused by F. oxysporum f. sp. ciceris

Fusarium wilt is caused by F. oxysporum Schlecht end. Fr. f. sp. ciceris (FOC) is a devastating disease of chickpea in Algeria. In this study, antagonistic effects of B. subtilis MF352017 (Bs1) and Trichoderma harzianum KX523899 (T5) isolated from the rhizosphere of chickpea were investigated separately and in combination for their efficacy in controlling the disease in vivo. The efficacy of the antagonistic biocontrol agents on Fusarium wilt was evaluated based on vegetative and root growth parameters of chickpea. Seed bacterisation with B. subtilis MF352017 (Bs1) and seed treatment with T. harzianum (T5) significantly protected chickpea seedlings from FOC as compared to untreated plants. Plant protection was more pronounced in T. harzianum-treated plants than in bacterised plants. The application of both antagonists effectively suppressed 93.67% of the disease and also enhanced plant growth leading to increased plant height, root length, fresh and dry weights of shoot and root. The mixture of antagonists increased the effectiveness of B. subtilis MF352017 (Bs1) isolate on Fusarium wilt and improved chickpea growth.     

Vector mosquito image classification using novel RIFS feature selection and machine learning models for disease epidemiology

Every year about one million people die due to diseases transmitted by mosquitoes. The infection is transmitted to a person when an infected mosquito stings, injecting the saliva into the human body. The best possible way to prevent a mosquito-borne infection till date is to save the humans from exposure to mosquito bites. This study proposes a Machine Learning (ML) and Deep Learning based system to detect the presence of two critical disease spreading classes of mosquitoes such as the Aedes and Culex. The proposed system will effectively aid in epidemiology to design evidence-based policies and decisions by analyzing the risks and transmission. The study proposes an effective methodology for the classification of mosquitoes using ML and CNN models. The novel RIFS has been introduced which integrates two types of feature selection techniques – the ROI-based image filtering and the wrappers-based FFS technique. Comparative analysis of various ML and deep learning models has been performed to determine the most appropriate model applicable based on their performance metrics as well as computational needs. Results prove that ETC outperformed among the all applied ML model by providing 0.992 accuracy while VVG16 has outperformed other CNN models by giving 0.986 of accuracy.     

A proteomic study of in-root interactions between chickpea pathogens: the root-knot nematode Meloidogyne artiellia and the soil-borne fungus Fusarium oxysporum f. sp. ciceris race 5

Fusarium wilt caused by the fungus Fusarium oxysporum f. sp. ciceris (Foc) is the main soil-borne disease limiting chickpea production. Management of this disease is achieved mainly by the use of resistant cultivars. However, co-infection of a Foc-resistant plant by the fungus and the root-knot nematode Meloidogyne artiellia (Ma) causes breakdown of the resistance and thus limits its efficacy in the control of Fusarium wilt. In this work we aimed to reveal key aspects of chickpea:Foc:Ma interactions, studying fungal- and nematode-induced changes in root proteins, using chickpea lines 'CA 336.14.3.0' and 'ICC 14216K' that show similar resistant (Foc race 5) and susceptible (Ma) responses to either pathogen alone but a differential response after co-infection with both pathogens. 'CA 336.14.3.0' and 'ICC 14216K' chickpea plants were challenged with Foc race 5 and Ma, either in single or in combined inoculations, and the root proteomes were analyzed by two-dimensional gel electrophoresis using three biological replicates. Pairwise comparisons of treatments indicated that 47 protein spots in 'CA 336.14.3.0' and 31 protein spots in 'ICC 14216K' underwent significant changes in intensity. The responsive protein spots tentatively identified by MALDI TOF-TOF MS (27 spots for 'CA 336.14.3.0' and 15 spots for 'ICC 14216K') indicated that same biological functions were involved in the responses of either chickpea line to Foc race 5 and Ma, although common as well as line-specific responsive proteins were found within the different biological functions. To the best of our knowledge, this is the first study at the root proteome level of chickpea response to a biotic stress imposed by single and joint infections by two major soil-borne pathogens.     

Transmission of seed-borne infection of chilli by Burkholderia solanacearum and effect of biological seed treatment on disease incidence

Abstract

A survey of chilli fields in the state of Karnataka, India, showed the presence of bacterial wilt disease in important chilli growing regions. The disease incidence ranged from 26?–?32%. The pathogen was isolated from infected plant material and seeds. Infected plant material showed the release of milky white bacterial ooze. Burkholderia solanacearum was detected from chilli seeds by liquid assay and its identity was confirmed by biochemical tests, hypersensitive reaction and pathogenicity tests. Seed transmission of the pathogen up to 45% was observed in seeds artificially infested with the pathogen. Among different tissues of the seed, endosperm showed the presence of the pathogen. Biological seed treatment with antagonistic Pseudomonas fluorescens significantly (p?=?0.05) improved the seed quality parameters under laboratory conditions and drastically reduced the bacterial wilt incidence under field conditions. Seed-borne nature, transmission and effect of Pseudomonas fluorescens in both the forms of pure culture and formulation on seed quality parameters and bacterial wilt incidence are discussed in the present work.     

Use of a Mini-Dome Bioassay and Grafting to Study Resistance of Chickpea to Ascochyta Blight

A mini‐dome bioassay was developed to study pathogenicity of Ascochyta rabiei and relative resistance of chickpea (Cicer arietanium). It was determined that the best condition for assaying pathogenicity of A. rabiei was to use 2 × 10⁵ spores/ml as inoculum and to maintain a leaf wetness period of 24 h under mini‐domes at a temperature between 16 and 22°C. This mini‐dome pathogenicity assay was used to determine relative resistance of six chickpea cultivars (cvs) to isolates of two pathotypes of A. rabiei. Grafting was employed to detect any translocated factors produced in the chickpea plant that mediate disease response, which could help elucidate possible resistance mechanisms to Ascochyta blight. The six chickpea cv. were grafted in all possible scion–rootstock combinations, and then inoculated with isolates of two pathotypes of A. rabiei using the mini‐dome technique. Results showed that self‐grafted‐resistant plants remained resistant and self‐grafted‐susceptible plants stayed susceptible, indicating the grafting procedure did not alter host response to infection by A. rabiei. Susceptible scions always exhibited high and similar levels of disease severity regardless of rootstock genotypes, and resistant scions always showed low and similar levels of disease severity when they were grafted onto any of the six rootstock genotypes. Orthogonal contrasts showed that scion genotypes determined disease phenotype, and that rootstock genotypes had no contribution to disease phenotype of the scions. The pathogenicity assay did not detect any translocated disease‐mediating agents responsible for susceptibility or resistance in chickpea. Disease phenotypes of Ascochyta blight of chickpea were conditioned locally by scion genotypes.     

Understanding Reaction of Potato (Solanum tuberosum) to Ralstonia solanacearum and Relationship of Wilt Incidence to Latent Infection

Bacterial wilt caused by Ralstonia solanacearum is one of the most important diseases affecting more than 200 plant species, including solanaceous crops. The pathogen is known to cause complicated symptoms ranging from visible to latent ones. Understanding crop's reaction to the pathogen and the underlying relatedness of latent infection to wilt incidence is of paramount importance. Thus, a number of potato cultivars including improved and otherwise were evaluated under greenhouse and field conditions. Accordingly, twenty‐eight of the cultivars tested under greenhouse conditions were resistant to the pathogen with scores ranging from 0.77 to 1.17 of 5. Nonetheless, under field conditions, only 2 of 28 cultivars found to be ‘resistant’ under greenhouse conditions, showed adequate resistance to the pathogen, indicating the significant impact of environment on the activity of the pathogen and reaction of the crop. Percentage wilt incidence and latent infection showed significant (P < 0.05) positive correlation, with r = 0.9438. Thus, evaluation of crop's performance based on the combination of the parameters like field wilt incidence and proportion of latent infection gave us better picture of the overall crop feat, than using wilt incidence as a sole parameter of evaluation as has been the case in most studies. Moreover, the established correlation of latent infection with field wilt incidence will also help us understand the disease epidemiology and design effective management measures, accordingly.     

Nontarget effects of foliar fungicide application on the rhizosphere: diversity of nifH gene and nodulation in chickpea field

Aims: This study explores nontarget effects of fungicide application on field‐grown chickpea. Methods and Results: Molecular methods were used to test the effects of foliar application of fungicide on the diversity and distribution of nifH genes associated with two chickpea cultivars and their nodulation. Treatments were replicated four times in a split‐plot design in the field, in 2008 and 2009. Chemical disease control did not change the richness of the nifH genes associated with chickpea, but selected different dominant nifH gene sequences in 2008, as revealed by correspondence analysis. Disease control strategies had no significant effect on disease severity or nifH gene distribution in 2009. Dry weather conditions rather than disease restricted plant growth that year, suggesting that reduced infection rather than the fungicide is the factor modifying the distribution of nifH gene in chickpea rhizosphere. Reduced nodule size and enhanced N₂‐fixation in protected plants indicate that disease control affects plant physiology, which may in turn influence rhizosphere bacteria. The genotypes of chickpea also affected the diversity of the nifH gene in the rhizosphere, illustrating the importance of plant selective effects on bacterial communities. Conclusions: We conclude that the chemical disease control affects nodulation and the diversity of nifH gene in chickpea rhizosphere, by modifying host plant physiology. A direct effect of fungicide on the bacteria cannot be ruled out, however, as residual amounts of fungicide were found to accumulate in the rhizosphere soil of protected plants. Significance and Impact of the Study: Systemic nontarget effect of phytoprotection on nifH gene diversity in chickpea rhizosphere is reported for the first time. This result suggests the possibility of manipulating associative biological nitrogen fixation in the field.     

Sequence similarity based identification of abiotic stress responsive genes in chickpea

Chickpea (Cicer arietinum L.) is an important food legume crop, particularly for the arid regions including Indian subcontinent. Considering the detrimental effect of drought, temperature and salt stress on crop yield, efforts have been initiated in the direction of developing improved varieties and designing alternate strategies to sustain chickpea production in adverse environmental conditions. Identification of genes that confer abiotic stress tolerance in plants remains a challenge in contemporary plant breeding. The present study focused on the identification of abiotic stress responsive genes in chickpea based on sequence similarity approach exploiting known abiotic stress responsive genes from model crops or other plant species. Ten abiotic stress responsive genes identified in other plants were partially amplified from eight chickpea genotypes and their presence in chickpea was confirmed after sequencing the PCR products. These genes have been functionally validated and reported to play significant role in stress response in model plants like Arabidopsis, rice and other legume crops. Chickpea EST sequences available at NCBI EST database were used for the identification of abiotic stress responsive genes. A total of 8,536 unique coding long sequences were used for identification of chickpea homologues of these abiotic stress responsive genes by sequence similarity search (BLASTN and BLASTX). These genes can be further explored towards achieving the goal of developing superior chickpea varieties providing improved yields under stress conditions using modern molecular breeding approaches.     

Control of chickpea wilt (Fusarium oxysporum f.sp. ciceris) using Trichoderma spp. in Ethiopia

Thirty-two Trichoderma isolates were collected from soils grown with chickpea in central highlands of Ethiopia. The eight isolates were identified by CAB-International as Trichoderma harzianum, T. koningii and T. pseudokoningii. In in vitro tests, all Trichoderma isolates showed significant (P < 0.05) differences in their colony growth and in inhibiting the colony growth of Fusarium oxysporum f.sp. ciceris, race 3. In potted experiment, four Trichoderma isolates were tested as seed treatment on three chickpea cultivars (JG-62 susceptible, Shasho moderately susceptible and JG-74 resistant) against F. oxysporum f.sp. ciceris, race 3. The result showed that T. harzianum and unidentified Trichoderma isolate T23 significantly reduced wilt severity and delayed disease onset. The degree of wilt severity and delay of disease onset varied with chickpea cultivars. Our study revealed that biological control agents such as Trichoderma can be a useful component of integrated chickpea Fusarium wilt management.     

Estimation of aboveground biomass using in situ hyperspectral measurements in five major grassland ecosystems on the Tibetan Plateau

Aims There are numerous grassland ecosystem types on the Tibetan Plateau. These include the alpine meadow and steppe and degraded alpine meadow and steppe. This study aimed at developing a method to estimate aboveground biomass (AGB) for these grasslands from hyperspectral data and to explore the feasibility of applying air/satellite-borne remote sensing techniques to AGB estimation at larger scales.Methods We carried out a field survey to collect hyperspectral reflectance and AGB for five major grassland ecosystems on the Tibetan Plateau and calculated seven narrow-band vegetation indices and the vegetation index based on universal pattern decomposition (VIUPD) from the spectra to estimate AGB. First, we investigated correlations between AGB and each of these vegetation indices to identify the best estimator of AGB for each ecosystem type. Next, we estimated AGB for the five pooled ecosystem types by developing models containing dummy variables. At last, we compared the predictions of simple regression models and the models containing dummy variables to seek an ecosystem type-independent model to improve prediction of AGB for these various grassland ecosystems from hyperspectral measurements.Important findings When we considered each ecosystem type separately, all eight vegetation indices provided good estimates of AGB, with the best predictor of AGB varying among different ecosystems. When AGB of all the five ecosystems was estimated together using a simple linear model, VIUPD showed the lowest prediction error among the eight vegetation indices. The regression models containing dummy variables predicted AGB with higher accuracy than the simple models, which could be attributed to the dummy variables accounting for the effects of ecosystem type on the relationship between AGB and vegetation index (VI). These results suggest that VIUPD is the best predictor of AGB among simple regression models. Moreover, both VIUPD and the soil-adjusted VI could provide accurate estimates of AGB with dummy variables integrated in regression models. Therefore, ground-based hyperspectral measurements are useful for estimating AGB, which indicates the potential of applying satellite/airborne remote sensing techniques to AGB estimation of these grasslands on the Tibetan Plateau.     

Fluid-structure interaction models based on patient-specific IVUS at baseline and follow-up for prediction of coronary plaque progression by morphological and biomechanical factors: A preliminary study

Plaque morphology and biomechanics are believed to be closely associated with plaque progression. In this paper, we test the hypothesis that integrating morphological and biomechanical risk factors would result in better predictive power for plaque progression prediction. A sample size of 374 intravascular ultrasound (IVUS) slices was obtained from 9 patients with IVUS follow-up data. 3D fluid-structure interaction models were constructed to obtain both structural stress/strain and fluid biomechanical conditions. Data for eight morphological and biomechanical risk factors were extracted for each slice. Plaque area increase (PAI) and wall thickness increase (WTI) were chosen as two measures for plaque progression. Progression measure and risk factors were fed to generalized linear mixed models and linear mixed-effect models to perform prediction and correlation analysis, respectively. All combinations of eight risk factors were exhausted to identify the optimal predictor(s) with highest prediction accuracy defined as sum of sensitivity and specificity. When using a single risk factor, plaque wall stress (PWS) at baseline was the best predictor for plaque progression (PAI and WTI). The optimal predictor among all possible combinations for PAI was PWS + PWSn + Lipid percent + Min cap thickness + Plaque Area (PA) + Plaque Burden (PB) (prediction accuracy = 1.5928) while Wall Thickness (WT) + Plaque Wall Strain (PWSn) + Plaque Area (PA) was the best for WTI (1.2589). This indicated that PAI was a more predictable measure than WTI. The combination including both morphological and biomechanical parameters had improved prediction accuracy, compared to predictions using only morphological features.     

Modelling the structural response of cotton plants to mepiquat chloride and population density

Background and Aims

Cotton (Gossypium hirsutum) has indeterminate growth. The growth regulator mepiquat chloride (MC) is used worldwide to restrict vegetative growth and promote boll formation and yield. The effects of MC are modulated by complex interactions with growing conditions (nutrients, weather) and plant population density, and as a result the effects on plant form are not fully understood and are difficult to predict. The use of MC is thus hard to optimize.

Methods

To explore crop responses to plant density and MC, a functional–structural plant model (FSPM) for cotton (named CottonXL) was designed. The model was calibrated using 1 year''s field data, and validated by using two additional years of detailed experimental data on the effects of MC and plant density in stands of pure cotton and in intercrops of cotton with wheat. CottonXL simulates development of leaf and fruits (square, flower and boll), plant height and branching. Crop development is driven by thermal time, population density, MC application, and topping of the main stem and branches.

Key Results

Validation of the model showed good correspondence between simulated and observed values for leaf area index with an overall root-mean-square error of 0·50 m² m⁻², and with an overall prediction error of less than 10 % for number of bolls, plant height, number of fruit branches and number of phytomers. Canopy structure became more compact with the decrease of leaf area index and internode length due to the application of MC. Moreover, MC did not have a substantial effect on boll density but increased lint yield at higher densities.

Conclusions

The model satisfactorily represents the effects of agronomic measures on cotton plant structure. It can be used to identify optimal agronomic management of cotton to achieve optimal plant structure for maximum yield under varying environmental conditions.     

Apical Chlorosis Disease of Chickpea (Cicer arietinum) Caused by Tomato Spotted Wilt Virus in Brazil

A severe new disease was observed in field-grown chickpea (Cicer arietinum L.) plants in Brasilia-DF, central Brazil. Symptoms were mainly general chlorosis accompanied by necrosis of the new growth and plant stunting, but pods were symptomless. Host range studies, serology, particle morphology, and cytopathology showed that tomato-spotted wilt tospovirus (TSWV) was the cause of the disease. This is apparently the first report of a chickpea disease caused by natural infection of a tospovirus.