Phytoplasma-Associated Diseases in South America: Thirty Years of Research.

Phytoplasma-associated diseases are mainly insect-transmitted and are present worldwide. Considering that disease detection is a relevant environmental factor that may elucidate the presence of these diseases, a review reporting the geographic distribution of phytoplasma taxa in geographically consistent areas helps manage diseases appropriately and reduce their spreading. This work summarizes the data available about the identification of the phytoplasma associated with several diverse diseases in South America in the last decades. The insect vectors and putative vectors together with the plant host range of these phytoplasmas are also summarized. Overall, 16 'Candidatus Phytoplasma' species were detected, and those most frequently detected in agricultural-relevant crops such as corn, alfalfa, grapevine, and other horticultural species are 'Ca. P. pruni', 'Ca. P. asteris', and 'Ca. P. fraxini'.

CRISPRals: A Web Database for Assessing the CRISPR Defense System in the Ralstonia solanacearum Species Complex to Avoid Phage Resistance.

Clustered regularly interspaced short palindromic repeats (CRISPR) has been widely characterized as a defense system against phages and other invading elements in bacteria and archaea. A low percentage of Ralstonia solanacearum species complex (RSSC) strains possess the CRISPR array and the CRISPR-associated proteins (Cas) that would confer immunity against various phages. To provide a wide-range screen of the CRISPR presence in the RSSC, we analyzed 378 genomes of RSSC strains to find the CRISPR locus. We found that 20.1, 14.3, and 54.5% of the R. solanacearum, R. pseudosolanacearum, and R. syzygii strains, respectively, possess the CRISPR locus. In addition, we performed further analysis to identify the respective phages that are restricted by the CRISPR arrays. We found 252 different phages infecting different strains of the RSSC, by means of the identification of similarities between the protospacers in phages and spacers in bacteria. We compiled this information in a database with web access called CRISPRals (https://crisprals.yachaytech.edu.ec/). Additionally, we made available a number of tools to detect and identify CRISPR array and Cas genes in genomic sequences that could be uploaded by users. Finally, a matching tool to relate bacteria spacer with phage protospacer sequences is available. CRISPRals is a valuable resource for the scientific community that contributes to the study of bacteria-phage interaction and a starting point that will help to design efficient phage therapy strategies.

Machine learning in the classification of asian rust severity in soybean using hyperspectral sensor.

Traditional monitoring of asian soybean rust severity is a time- and labor-intensive task, as it requires visual assessments by skilled professionals in the field. Thus, the use of remote sensing and machine learning (ML) techniques in data processing has emerged as an approach that can increase efficiency in disease monitoring, enabling faster, more accurate and time- and labor-saving evaluations. The aims of the study were: (i) to identify the spectral signature of different levels of Asian soybean rust severity; (ii) to identify the most accurate machine learning algorithm for classifying disease severity levels; (iii) which spectral input provides the highest classification accuracy for the algorithms; (iv) to determine a sample size of leaves that guarantees the best accuracy for the algorithms. A field experiment was carried out in the 2022/2023 harvest in a randomized block design with a 6x3 factorial scheme (ML algorithms x severity levels) and four replications. Disease severity levels assessed were: healthy leaves, 25 % severity, and 50 % severity. Leaf hyperspectral analysis was carried out over a wide range from 350 to 2500 nm. From this analysis, 28 spectral bands were extracted, seeking to distinguish the spectral signature for each severity level with the least input dataset. Data was subjected to machine learning analysis using Artificial Neural Network (ANN), REPTree (DT) and J48 decision trees, Random Forest (RF), and Support Vector Machine (SVM) algorithms, as well as a traditional classification method (Logistic Regression - LR). Two different input datasets were tested for each algorithm: the full spectrum (ALL) provided by the sensor and the 28 spectral bands (SB). Tests with different sample sizes were also conducted to investigate the algorithms' ability to detect severity levels with a reduced sample size. Our findings indicate differences between the spectral curves for the severity levels assessed, which makes it possible to differentiate between healthy plants with low and high severity using hyperspectral sensing. SVM was the most accurate algorithm for classifying severity levels by using all the spectral information as input. This algorithm also provided high classification accuracy when using smaller leaf samples. This study reveals that hyperspectral sensing and the use of ML algorithms provide an accurate classification of different levels of Asian rust severity, and can be powerful tools for a more efficient disease monitoring process.

What's in my Pot? Six Colletotrichum Species Causing Anthracnose in Brazilian Pecan Orchards.

Pecan (Carya illinoinensis) is one important exotic forest crop cultivated in South America, specifically in Brazil, Uruguay, and Argentina. However, diseases such as anthracnose, favored by high humidity conditions and high summer temperatures, make its cultivation difficult, causing important loss to pecan farmers. This study used morphological and molecular approaches to identify the Colletotrichum species causing anthracnose in pecan plantations in Southern Brazil. The isolates obtained from pecan fruits with anthracnose symptoms were grouped through quantitative morphological characteristics into three distinct morphotypes. Molecular analysis of nuclear genes allowed the identification of six species of Colletotrichum causing anthracnose in pecan: C. nymphaeae, C. fioriniae, C. gloeosporioides, C. siamense, C. kahawae, and C. karsti. Three of these species are reported for the first time as causal agents of anthracnose in pecan. Therefore, these results provide an important basis for the adoption and/or development of anthracnose management strategies in pecan orchards cultivated in southern Brazil and neighboring countries.

Fungitoxic effect and phytochemical characteristics of Brazilian Cerrado weeds against Rhizoctonia solani and Macrophomina phaseolina fungi / Efeito fungitóxico e características fitoquímicas de plantas daninhas do Cerrado brasileiro frente aos fungos Rhizoctonia solani e Macrophomina phaseolina

The use of natural products obtained from plants, for example, invasive plants, offers a variety of allelochemicals with fungicidal potential. With this in perspective, the objective was to evaluate the fungicidal potential of ethanolic extracts of Cerrado plants on Rhizoctonia solani and Macrophomina phaseolina. The ethanolic hydroalcoholic extract of the 12 plants identified as invaders in the Brazilian Cerrado was prepared (Anacardium humile Saint Hill; Baccharis dracunculifolia DC.; Cenchrus echinatus L; Commelina erecta L.; Erigeron bonariensis L.; Digitaria horizontalis Willd.; Digitaria insularis L.; Porophyllum ruderale Jacq. Cass; Richardia brasiliensis Gomes; Sida rhombifolia L.; Turnera ulmifolia L.; Smilax fluminensis Steud)) and phytochemical screening and determination of total phenols and flavonoids were performed. To evaluate the in vitro antifungal activity, the hydroalcoholic solutions at concentrations of 800, 1200, 1600, 2000, and 2400 µL 100 mL-1 were separately incorporated into BDA agar and poured into Petri dishes, followed by the mycelium disk of the fungus. As a control, two solutions were prepared, one ethanolic solution added to the BDA medium (2400 µg 100 mL-1) and the other with BDA medium only. They were poured into Petri dishes, followed by a 0.5 cm diameter disk of mycelium of the fungus, incubated (23±2 ºC), with a 24-hour photoperiod. Among the constituents found in the plants, 75% are phenolic compounds, 58.3% are cardiotonic heterosides, 50% are steroids, 33.3% are flavonoids, 16.7% are anthraquinones, and 8.3% are alkaloids, saponins, and reducing sugars. Out of the 12 species, only the extracts of C. erecta and R. brasiliensis were active for M. phaseolina and R. solani. Thus, it is concluded that the ethanolic extract of C. erecta has the fungicidal potential to control diseases caused by fungi that are soil inhabitants. Of the other species, A. humille, B. dracuncufolia, D. insulares, C. erecta, D. insulares, P. ruderale, and R. brasiliensis have natural fungitoxic potential because they stand out in the content of polyphenols efficient in reducing the mycelial growth of M. phaseolina and R. solani.

O uso de produtos naturais obtidos de plantas, por exemplo, as plantas invasoras, oferece uma variedade de aleloquímicos com potencial fungicida. Tendo isso em vista, objetivou-se avaliar o potencial fungicida de extratos etanólicos de plantas do Cerrado sobre Rhizoctonia solani e Macrophomina phaseolina. Foi preparado o extrato hidroalcoólicos etanólico das 12 plantas apontadas como invasoras no Cerrado brasileiro (Anacardium humile Saint Hill; Baccharis dracunculifolia DC.; Cenchrus echinatus L; Commelina erecta L.; Erigeron bonariensis L.; Digitaria horizontalis Willd.; Digitaria insularis L.; Porophyllum ruderale Jacq. Cass; Richardia brasiliensis Gomes; Sida rhombifolia L.; Turnera ulmifolia L.; Smilax fluminensis Steud) e foi realizado o screening fitoquímico e a determinação de fenóis e flavonoides totais. Para avaliar a atividade antifúngica in vitro, as soluções hidroalcóolicas nas concentrações de 800, 1200, 1600, 2000 e 2400 µL 100 mL-1 foram incorporadas, separadamente, em ágar BDA, e vertidas em placa de Petri, seguido do disco de micélio do fungo. Como controle, foram preparadas duas soluções, uma solução etanólica adicionada ao meio BDA (2400 µg 100 mL-1), e outra somente com meio BDA, a testemunha. Foram vertidas em placas de Petri, seguido um disco de 0,5 cm de diâmetro de micélio do fungo, incubados (23±2 ºC), com fotoperíodo de 24 horas. Dentre os constituintes encontrados nas plantas, 75% estão os compostos fenólicos, 58,3% estão os heterosídeos cardiotônicos, 50% estão os esteroides, 33,3% estão os flavonoides, 16,7% estão as antraquinonas e 8,3% estão os alcaloides, saponinas e açúcares redutores. Das 12 espécies, apenas os extratos de C. erecta e R. brasiliensis foram ativos para M. phaseolina e R. solani. Desse modo, conclui-se que o extrato etanólico de C. erecta apresenta potencial fungicida para controle de doenças causadas por fungos habitantes do solo. Das demais espécies, a A. humille, B. dracuncufolia, D. insulares, C. erecta, D. insulares, P. ruderale e R. brasiliensis possuem potencial fungitóxicos naturais por destacarem nos teores de polifenóis eficientes na redução do crescimento micelial de M. phaseolina e R. solani.

Repeated exposure of wheat to the fungal root pathogen Bipolaris sorokiniana modulates rhizosphere microbiome assembly and disease suppressiveness.

BACKGROUND: Disease suppressiveness of soils to fungal root pathogens is typically induced in the field by repeated infections of the host plant and concomitant changes in the taxonomic composition and functional traits of the rhizosphere microbiome. Here, we studied this remarkable phenomenon for Bipolaris sorokiniana in two wheat cultivars differing in resistance to this fungal root pathogen. RESULTS: The results showed that repeated exposure of the susceptible wheat cultivar to the pathogen led to a significant reduction in disease severity after five successive growth cycles. Surprisingly, the resistant wheat cultivar, initially included as a control, showed the opposite pattern with an increase in disease severity after repeated pathogen exposure. Amplicon analyses revealed that the bacterial families Chitinophagaceae, Anaerolineaceae and Nitrosomonadaceae were associated with disease suppressiveness in the susceptible wheat cultivar; disease suppressiveness in the resistant wheat cultivar was also associated with Chitinophagaceae and a higher abundance of Comamonadaceae. Metagenome analysis led to the selection of 604 Biosynthetic Gene Clusters (BGCs), out of a total of 2,571 identified by AntiSMASH analysis, that were overrepresented when the soil entered the disease suppressive state. These BGCs are involved in the biosynthesis of terpenes, non-ribosomal peptides, polyketides, aryl polyenes and post-translationally modified peptides. CONCLUSION: Combining taxonomic and functional profiling we identified key changes in the rhizosphere microbiome during disease suppression. This illustrates how the host plant relies on the rhizosphere microbiome as the first line of defense to fight soil-borne pathogens. Microbial taxa and functions identified here can be used in novel strategies to control soil-borne fungal pathogens.

Transmission of Xanthomonas albilineans by the spittlebug, Mahanarva fimbriolata (Hemiptera: Cercopidae), in Brazil: first report of an insect vector for the causal agent of sugarcane leaf scald.

Leaf scald is a destructive sugarcane disease caused by the bacterium Xanthomonas albilineans (Ashby) Dowson. This pathogen presents the gene cluster SPI-1 T3SS, a conserved feature in pathogens vectored by animals. In this study, the competence of Mahanarva fimbriolata (Stål), a spittlebug commonly found in sugarcane fields in Brazil, was evaluated for the transmission of X. albilineans. Artificial probing assays were conducted to investigate the ability of M. fimbriolata adults to acquire X. albilineans from artificial diets containing the pathogen with subsequent inoculation of X. albilineans into pathogen-free diets. Plant probing assays with M. fimbriolata adults were conducted to evaluate the acquisition of X. albilineans from diseased source plants and subsequent inoculation of healthy recipient sugarcane plants. The presence of X. albilineans DNA in saliva/diet mixtures of the artificial probing assays and both insects and plants of the plant probing assays were checked using TaqMan assays. The artificial probing assays showed that M. fimbriolata adults were able to acquire and inoculate X. albilineans in diets. Plant probing assays confirmed the competence of M. fimbriolata to transmit X. albilineans to sugarcane. Over the entire experiment, 42% of the insects had acquired the pathogen and successful inoculation of the pathogen occurred in 18% of the recipient-susceptible sugarcane plants at 72 or 96 h of inoculation access period. Assays evidenced the vector competence of M. fimbriolata for transmission of X. albilineans, opening new pathways for investigating the biology and the economic impacts of the interaction between X. albilineans and M. fimbriolata.

Interactions of Different Species of Phytophthora with Cacao Induce Genetic, Biochemical, and Morphological Plant Alterations.

Diseases associated with Phytophthora cause considerable losses in cocoa production worldwide. Analyzing genes, proteins, and metabolites involved in Theobroma cacao's interaction with Phytophthora species is essential to explaining the molecular aspects of plant defense. Through a systematic literature review, this study aims to identify reports of genes, proteins, metabolites, morphological characteristics, and molecular and physiological processes of T. cacao involved in its interaction with species of Phytophthora. After the searches, 35 papers were selected for the data extraction stage, according to pre-established inclusion and exclusion criteria. In these studies, 657 genes and 32 metabolites, among other elements (molecules and molecular processes), were found to be involved in the interaction. The integration of this information resulted in the following conclusions: the expression patterns of pattern recognition receptors (PRRs) and a possible gene-to-gene interaction participate in cocoa resistance to Phytophthora spp.; the expression pattern of genes that encode pathogenesis-related (PRs) proteins is different between resistant and susceptible genotypes; phenolic compounds play an important role in preformed defenses; and proline accumulation may be involved in cell wall integrity. Only one proteomics study of T. cacao-Phytophthora spp. was found, and some genes proposed via QTL analysis were confirmed in transcriptomic studies.

Characterizing the vector competence of Aphis gossypii, Myzus persicae and Aphis craccivora (Hemiptera: Aphididae) to transmit cotton leafroll dwarf virus to cotton in the United States.

Cotton leafroll dwarf virus (CLRDV) is a yield-limiting, aphid-transmitted virus that was identified in cotton, Gossypium hirsutum L., in the United States of America in 2017. CLRDV is currently classified in the genus Polerovirus, family Solemoviridae. Although 8 species of aphids (Hemiptera: Aphididae) are reported to infest cotton, Aphis gossypii Glover is the only known vector of CLRDV to this crop. Aphis gossypii transmits CLRDV in a persistent and nonpropagative manner, but acquisition and retention times have only been partially characterized in Brazil. The main objectives of this study were to characterize the acquisition access period, the inoculation access period, and retention times for a U.S. strain of CLRDV and A. gossypii population. A sub-objective was to test the vector competence of Myzus persicae Sulzer and Aphis craccivora Koch. In our study, A. gossypii apterous and alate morphs were able to acquire CLRDV in 30 min and 24 h, inoculate CLRDV in 45 and 15 min, and retain CLRDV for 15 and 23 days, respectively. Neither M. persicae nor A. craccivora acquired or transmitted CLRDV to cotton.

Sphingolipid Long-Chain Base Signaling in Compatible and Non-Compatible Plant-Pathogen Interactions in Arabidopsis.

The chemical diversity of sphingolipids in plants allows the assignment of specific roles to special molecular species. These roles include NaCl receptors for glycosylinositolphosphoceramides or second messengers for long-chain bases (LCBs), free or in their acylated forms. Such signaling function has been associated with plant immunity, with an apparent connection to mitogen-activated protein kinase 6 (MPK6) and reactive oxygen species (ROS). This work used in planta assays with mutants and fumonisin B1 (FB1) to generate varying levels of endogenous sphingolipids. This was complemented with in planta pathogenicity tests using virulent and avirulent Pseudomonas syringae strains. Our results indicate that the surge of specific free LCBs and ceramides induced by FB1 or an avirulent strain trigger a biphasic ROS production. The first transient phase is partially produced by NADPH oxidase, and the second is sustained and is related to programmed cell death. MPK6 acts downstream of LCB buildup and upstream of late ROS and is required to selectively inhibit the growth of the avirulent but not the virulent strain. Altogether, these results provide evidence that a LCB- MPK6- ROS signaling pathway contributes differentially to the two forms of immunity described in plants, upregulating the defense scheme of a non-compatible interaction.

Assessing the Biocontrol Potential of Clonostachys Species Isolated as Endophytes from Coffea Species and as Mycoparasites of Hemileia Rusts of Coffee in Africa.

During surveys conducted in South America and Africa to identify natural fungal enemies of coffee leaf rust (CLR), Hemileia vastatrix, over 1500 strains were isolated, either as endophytes from healthy tissues of Coffea species or as mycoparasites growing on rust pustules. Based on morphological data, eight isolates-three isolated from wild or semiwild coffee and five from Hemileia species on coffee, all from Africa-were provisionally assigned to the genus Clonostachys. A polyphasic study of their morphological, cultural and molecular characteristics-including the Tef1 (translation elongation factor 1 alpha), RPB1 (largest subunit of RNA polymerase II), TUB (ß-tubulin) and ACL1 (ATP citrate lyase) regions-confirmed these isolates as belonging to three species of the genus Clonostachys: namely C. byssicola, C. rhizophaga and C. rosea f. rosea. Preliminary assays were also conducted to test the potential of the Clonostachys isolates to reduce CLR severity on coffee under greenhouse conditions. Foliar and soil applications indicated that seven of the isolates had a significant effect (p < 0.05) in reducing CLR severity. In parallel, in vitro tests that involved conidia suspensions of each of the isolates together with urediniospores of H. vastatrix resulted in high levels of inhibition of urediniospore germination. All eight isolates showed their ability to establish as endophytes in C. arabica during this study, and some proved to be mycoparasites of H. vastatrix. In addition to reporting the first records of Clonostachys associated with healthy coffee tissues and with Hemileia rusts of coffee, this work provides the first evidence that Clonostachys isolates have potential as biological control agents against CLR.

Fungal Effectoromics: A World in Constant Evolution.

Effectors are small, secreted molecules that mediate the establishment of interactions in nature. While some concepts of effector biology have stood the test of time, this area of study is ever-evolving as new effectors and associated characteristics are being revealed. In the present review, the different characteristics that underly effector classifications are discussed, contrasting past and present knowledge regarding these molecules to foster a more comprehensive understanding of effectors for the reader. Research gaps in effector identification and perspectives for effector application in plant disease management are also presented, with a focus on fungal effectors in the plant-microbe interaction and interactions beyond the plant host. In summary, the review provides an amenable yet thorough introduction to fungal effector biology, presenting noteworthy examples of effectors and effector studies that have shaped our present understanding of the field.

Genome-wide association study for resistance to Pseudomonas syringae pv. garcae in Coffea arabica.

Bacteria halo blight (BHB), a coffee plant disease caused by Pseudomonas syringae pv. garcae, has been gaining importance in producing mountain regions and mild temperatures areas as well as in coffee nurseries. Most Coffea arabica cultivars are susceptible to this disease. In contrast, a great source of genetic diversity and resistance to BHB are found in C. arabica Ethiopian accessions. Aiming to identify quantitative trait nucleotides (QTNs) associated with resistance to BHB and the influence of these genomic regions during the domestication of C. arabica, we conducted an analysis of population structure and a Genome-Wide Association Study (GWAS). For this, we used genotyping by sequencing (GBS) and phenotyping for resistance to BHB of a panel with 120 C. arabica Ethiopian accessions from a historical FAO collection, 11 C. arabica cultivars, and the BA-10 genotype. Population structure analysis based on single-nucleotide polymorphisms (SNPs) markers showed that the 132 accessions are divided into 3 clusters: most wild Ethiopian accessions, domesticated Ethiopian accessions, and cultivars. GWAS, using the single-locus model MLM and the multi-locus models mrMLM, FASTmrMLM, FASTmrEMMA, and ISIS EM-BLASSO, identified 11 QTNs associated with resistance to BHB. Among these QTNs, the four with the highest values of association for resistance to BHB are linked to g000 (Chr_0_434_435) and g010741 genes, which are predicted to encode a serine/threonine-kinase protein and a nucleotide binding site leucine-rich repeat (NBS-LRR), respectively. These genes displayed a similar transcriptional downregulation profile in a C. arabica susceptible cultivar and in a C. arabica cultivar with quantitative resistance, when infected with P. syringae pv. garcae. However, peaks of upregulation were observed in a C. arabica cultivar with qualitative resistance, for both genes. Our results provide SNPs that have potential for application in Marker Assisted Selection (MAS) and expand our understanding about the complex genetic control of the resistance to BHB in C. arabica. In addition, the findings contribute to increasing understanding of the C. arabica domestication history.

Microbial Effectors: Key Determinants in Plant Health and Disease.

Effectors are small, secreted molecules that alter host cell structure and function, thereby facilitating infection or triggering a defense response. Effectoromics studies have focused on effectors in plant-pathogen interactions, where their contributions to virulence are determined in the plant host, i.e., whether the effector induces resistance or susceptibility to plant disease. Effector molecules from plant pathogenic microorganisms such as fungi, oomycetes and bacteria are major disease determinants. Interestingly, the effectors of non-pathogenic plant organisms such as endophytes display similar functions but have different outcomes for plant health. Endophyte effectors commonly aid in the establishment of mutualistic interactions with the plant and contribute to plant health through the induction of systemic resistance against pathogens, while pathogenic effectors mainly debilitate the plant's immune response, resulting in the establishment of disease. Effectors of plant pathogens as well as plant endophytes are tools to be considered in effectoromics for the development of novel strategies for disease management. This review aims to present effectors in their roles as promotors of health or disease for the plant host.

Effective Methods Based on Distinct Learning Principles for the Analysis of Hyperspectral Images to Detect Black Sigatoka Disease.

Current chemical methods used to control plant diseases cause a negative impact on the environment and increase production costs. Accurate and early detection is vital for designing effective protection strategies for crops. We evaluate advanced distributed edge intelligence techniques with distinct learning principles for early black sigatoka disease detection using hyperspectral imaging. We discuss the learning features of the techniques used, which will help researchers improve their understanding of the required data conditions and identify a method suitable for their research needs. A set of hyperspectral images of banana leaves inoculated with a conidial suspension of black sigatoka fungus (Pseudocercospora fijiensis) was used to train and validate machine learning models. Support vector machine (SVM), multilayer perceptron (MLP), neural networks, N-way partial least square-discriminant analysis (NPLS-DA), and partial least square-penalized logistic regression (PLS-PLR) were selected due to their high predictive power. The metrics of AUC, precision, sensitivity, prediction, and F1 were used for the models' evaluation. The experimental results show that the PLS-PLR, SVM, and MLP models allow for the successful detection of black sigatoka disease with high accuracy, which positions them as robust and highly reliable HSI classification methods for the early detection of plant disease and can be used to assess chemical and biological control of phytopathogens.

Draft genome sequence of Bacillus sp. strain FSQ1, a biological control agent against white mold in common bean (Phaseolus vulgaris L.).

Bacillus sp. strain FSQ1 was isolated from the common bean (Phaseolus vulgaris L.). The genome of this strain presented 3,598,499 bp; 43.0% G + C content; 925,913 bp N50; 2 L50; 33 contigs; 97 RNAs and 3,908 predicted coding DNA sequences (CDS) distributed in 315 subsystems. Based on genome mining, the biological control activity of strains FSQ1 could be associated with the biosynthesis of rhizocticin A and bacillibactin. Thus, this strain is a promising active ingredient for the formulation of biopesticides.

Understanding the ramifications of quantitative ordinal scales on accuracy of estimates of disease severity and data analysis in plant pathology.

The severity of plant diseases, traditionally defined as the proportion of the plant tissue exhibiting symptoms, is a key quantitative variable to know for many diseases but is prone to error. Plant pathologists face many situations in which the measurement by nearest percent estimates (NPEs) of disease severity is time-consuming or impractical. Moreover, rater NPEs of disease severity are notoriously variable. Therefore, NPEs of disease may be of questionable value if severity cannot be determined accurately and reliably. In such situations, researchers have often used a quantitative ordinal scale of measurement-often alleging the time saved, and the ease with which the scale can be learned. Because quantitative ordinal disease scales lack the resolution of the 0 to 100% scale, they are inherently less accurate. We contend that scale design and structure have ramifications for the resulting analysis of data from the ordinal scale data. To minimize inaccuracy and ensure that there is equivalent statistical power when using quantitative ordinal scale data, design of the scales can be optimized for use in the discipline of plant pathology. In this review, we focus on the nature of quantitative ordinal scales used in plant disease assessment. Subsequently, their application and effects will be discussed. Finally, we will review how to optimize quantitative ordinal scales design to allow sufficient accuracy of estimation while maximizing power for hypothesis testing.

Raman Spectroscopy and Machine-Learning for Early Detection of Bacterial Canker of Tomato: The Asymptomatic Disease Condition.

Bacterial canker of tomato is caused by Clavibacter michiganensis subsp. michiganensis (Cmm). The disease is highly destructive, because it produces latent asymptomatic infections that favor contagion rates. The present research aims consisted on the implementation of Raman spectroscopy (RS) and machine-learning spectral analysis as a method for the early disease detection. Raman spectra were obtained from infected asymptomatic tomato plants (BCTo) and healthy controls (HTo) with 785 nm excitation laser micro-Raman spectrometer. Spectral data were normalized and processed by principal component analysis (PCA), then the classifiers algorithms multilayer perceptron (PCA + MLP) and linear discriminant analysis (PCA + LDA) were implemented. Bacterial isolation and identification (16S rRNA gene sequencing) were realized of each plant studied. The Raman spectra obtained from tomato leaf samples of HTo and BCTo exhibited peaks associated to cellular components, and the most prominent vibrational bands were assigned to carbohydrates, carotenoids, chlorophyll, and phenolic compounds. Biochemical changes were also detectable in the Raman spectral patterns. Raman bands associated with triterpenoids and flavonoids compounds can be considered as indicators of Cmm infection during the asymptomatic stage. RS is an efficient, fast and reliable technology to differentiate the tomato health condition (BCTo or HTo). The analytical method showed high performance values of sensitivity, specificity and accuracy, among others.

Context-Dependent Effects of Trichoderma Seed Inoculation on Anthracnose Disease and Seed Yield of Bean (Phaseolus vulgaris): Ambient Conditions Override Cultivar-Specific Differences.

Root colonizing Trichoderma fungi can stimulate plant immunity, but net effects are strain × cultivar-specific and changing ambient conditions further contribute to variable outcomes. Here, we used four Trichoderma spp. to inoculate seeds of four common bean (Phaseolus vulgaris) cultivars and explored in three different experimental setups the effects on fungal anthracnose after leaf inoculation with Colletotrichum lindemuthianum. Plants growing in pots with field soil under greenhouse conditions exhibited the highest and those in the open field the lowest overall levels of disease. Among 48 Trichoderma strain × bean cultivar × setup combinations, Trichoderma-inoculation enhanced disease in six and decreased disease in ten cases, but with the exception of T. asperellum B6-inoculated Negro San Luis beans, the strain × cultivar-specific effects on anthracnose severity differed among the setups, and anthracnose severity did not predict seed yield in the open field. In the case of Flor de Mayo beans, Trichoderma even reduced yield in anthracnose-free field plots, although this effect was counterbalanced in anthracnose-infected plots. We consider our work as a case study that calls for stronger emphasis on field experiments in the early phases of screenings of Trichoderma inoculants as plant biostimulants.

Endophytic Fungi: Biological Control and Induced Resistance to Phytopathogens and Abiotic Stresses.

Plant diseases cause losses of approximately 16% globally. Thus, management measures must be implemented to mitigate losses and guarantee food production. In addition to traditional management measures, induced resistance and biological control have gained ground in agriculture due to their enormous potential. Endophytic fungi internally colonize plant tissues and have the potential to act as control agents, such as biological agents or elicitors in the process of induced resistance and in attenuating abiotic stresses. In this review, we list the mode of action of this group of microorganisms which can act in controlling plant diseases and describe several examples in which endophytes were able to reduce the damage caused by pathogens and adverse conditions. This is due to their arsenal of molecules generated during the interaction by which they form a kind of biological shield in the plant. Furthermore, considering that endophytic fungi can be an important tool in managing for biotic and abiotic stresses due to the large amount of biologically active substances produced, bioprospecting this class of microorganisms is tending to increase and generate valuable products for agriculture.