RGB image-based method for phenotyping rust disease progress in pea leaves using R.

BACKGROUND: Rust is a damaging disease affecting vital crops, including pea, and identifying highly resistant genotypes remains a challenge. Accurate measurement of infection levels in large germplasm collections is crucial for finding new resistance sources. Current evaluation methods rely on visual estimation of disease severity and infection type under field or controlled conditions. While they identify some resistance sources, they are error-prone and time-consuming. An image analysis system proves useful, providing an easy-to-use and affordable way to quickly count and measure rust-induced pustules on pea samples. This study aimed to develop an automated image analysis pipeline for accurately calculating rust disease progression parameters under controlled conditions, ensuring reliable data collection. RESULTS: A highly efficient and automatic image-based method for assessing rust disease in pea leaves was developed using R. The method's optimization and validation involved testing different segmentation indices and image resolutions on 600 pea leaflets with rust symptoms. The approach allows automatic estimation of parameters like pustule number, pustule size, leaf area, and percentage of pustule coverage. It reconstructs time series data for each leaf and integrates daily estimates into disease progression parameters, including latency period and area under the disease progression curve. Significant variation in disease responses was observed between genotypes using both visual ratings and image-based analysis. Among assessed segmentation indices, the Normalized Green Red Difference Index (NGRDI) proved fastest, analysing 600 leaflets at 60% resolution in 62 s with parallel processing. Lin's concordance correlation coefficient between image-based and visual pustule counting showed over 0.98 accuracy at full resolution. While lower resolution slightly reduced accuracy, differences were statistically insignificant for most disease progression parameters, significantly reducing processing time and storage space. NGRDI was optimal at all time points, providing highly accurate estimations with minimal accumulated error. CONCLUSIONS: A new image-based method for monitoring pea rust disease in detached leaves, using RGB spectral indices segmentation and pixel value thresholding, improves resolution and precision. It rapidly analyses hundreds of images with accuracy comparable to visual methods and higher than other image-based approaches. This method evaluates rust progression in pea, eliminating rater-induced errors from traditional methods. Implementing this approach to evaluate large germplasm collections will improve our understanding of plant-pathogen interactions and aid future breeding for novel pea cultivars with increased rust resistance.

Validation of Standard Area Diagrams to Estimate the Severity of Septoria Leaf Spot on Stevia in Paraguay, Mexico, and the United States.

Septoria leaf spot (SLS) affects stevia leaves, reducing their quality. Estimates of SLS severity on different genotypes are made to identify resistance and as a basis to compare management approaches. The use of standard area diagrams (SADs) can improve the accuracy and reliability of severity estimates. In this study, we developed new SADs with six illustrations (0.5, 1, 10, 25, 40, and 75% severity). The SADs were validated by raters with and without experience in estimating SLS. Raters evaluated 40 leaf photos with SLS severities ranging from 0 to 100% without and with the SADs. Agreement (ρc), bias (Cb), precision (r), and intracluster correlation (ρ) coefficients were significantly closer to "true" severity values when the SADs was used by inexperienced (ρc = 0.89; Cb = 0.97; r = 0.90, ρ = 0.81) and experienced (ρc = 0.94; Cb = 0.99; r = 0.95, ρ = 0.91) raters. The SADs were tested under field conditions in Paraguay, Mexico, and the United States, with inexperienced raters assigned to two groups, one SADs trained and the other not trained, that estimated SLS severity three times: first, all raters without SADs and no time limit for the estimates; second, only the SADs-trained group used SADs and no time limit; and third, only the SADs-trained group used SADs, with a time limit of 10 s imposed per specimen assessment. Agreement and reliability of SLS severity estimates significantly improved when raters used the SADs without a time limit. The use of the new SADs improved the accuracy, precision, and reliability of SLS severity estimates, enhancing the uniformity in assessment across different stevia programs.

Automated, image-based disease measurement for phenotyping resistance to soybean frogeye leaf spot.

BACKGROUND: Frogeye leaf spot is a disease of soybean, and there are limited sources of crop genetic resistance. Accurate quantification of resistance is necessary for the discovery of novel resistance sources, which can be accelerated by using a low-cost and easy-to-use image analysis system to phenotype the disease. The objective herein was to develop an automated image analysis phenotyping pipeline to measure and count frogeye leaf spot lesions on soybean leaves with high precision and resolution while ensuring data integrity. RESULTS: The image analysis program developed measures two traits: the percent of diseased leaf area and the number of lesions on a leaf. Percent of diseased leaf area is calculated by dividing the number of diseased pixels by the total number of leaf pixels, which are segmented through a series of color space transformations and pixel value thresholding. Lesion number is determined by counting the number of objects remaining in the image when the lesions are segmented. Automated measurement of the percent of diseased leaf area deviates from the manually measured value by less than 0.05% on average. Automatic lesion counting deviates by an average of 1.6 lesions from the manually counted value. The proposed method is highly correlated with a conventional method using a 1-5 ordinal scale based on a standard area diagram. Input image compression was optimal at a resolution of 1500 × 1000 pixels. At this resolution, the image analysis method proposed can process an image in less than 10 s and is highly concordant with uncompressed images. CONCLUSION: Image analysis provides improved resolution over conventional methods of frogeye leaf spot disease phenotyping. This method can improve the precision and resolution of phenotyping frogeye leaf spot, which can be used in genetic mapping to identify QTLs for crop genetic resistance and in breeding efforts for resistance to the disease.

Diagrammatic scales for the estimation of black node disease severity in common bean / Escalas diagramáticas para a estimativa da gravidade da doença do nó negro no feijão comum

ABSTRACT: The objective of this study was to design two diagrammatic scales for the evaluation of black node disease (Stagonosporopsis hortensis and Boeremia spp.) in common bean (Phaseolus vulgaris L.). The developed scales corresponded to logarithmic intervals (SADL) of seven levels and equal intervals (SADE) of nine levels. These scales were compared to the scale developed by the International Center for Tropical Agriculture (CIAT), which corresponds to a descriptive scale (NoSAD). In the scale validation the accuracy, precision, and concordance of repeatability were determined using Lin's concordance correlation coefficient, whereas inter-rater reproducibility was determined by the overall concordance correlation coefficient (OCCC). It was observed that with the use of the proposed scales, reproducibility and repeatability were significantly improved for inexperienced raters, and reproducibility was improved in the case of experienced raters. Thus, the designed standard area diagrams with equal and logarithmic intervals are a useful tool for estimating severity under field and experimental conditions as part of the study of this patho-system.

RESUMO: O objetivo deste estudo foi delinear duas escalas diagramáticas para avaliação da doença do nó preto (Stagonosporopsis hortensis e Boeremia spp.) em feijoeiro (Phaseolus vulgaris L.). As escalas desenvolvidas corresponderam a intervalos logarítmicos (SADL) de sete níveis e intervalos iguais (SADE) de nove níveis. Essas escalas foram comparadas com a escala desenvolvida pelo Centro Internacional de Agricultura Tropical (CIAT), que corresponde a uma escala descritiva (NoSAD). Na validação da escala, a exatidão, precisão e concordância da repetibilidade foram determinadas usando o coeficiente de correlação de concordância de Lin, enquanto a reprodutibilidade entre avaliadores foi determinada pelo coeficiente de correlação de concordância geral (OCCC). Observou-se que, com o uso das escalas propostas, a reprodutibilidade e a repetibilidade foram significativamente melhoradas para os avaliadores inexperientes, e a reprodutibilidade foi melhorada no caso dos avaliadores experientes. Assim, as escalas diagramáticas projetadas são uma ferramenta útil para estimar a severidade em condições experimentais e de campo como parte do estudo desse sistema patológico.

Standard area diagram set for scab quantification in trilobed leaves of the sour passion fruit / Escala diagramática para a quantificação da verrugose em folhas trilobadas do maracujazeiro azedo

ABSTRACT: The study aimed to develop and validate a standard area diagram set (SADs) to improve accuracy, precision, and reproducibility in the assessment of scab severity in trilobed leaves of the sour passion fruit. The SADs comprised six severity levels (1%; 3%; 6%; 11%; 21%; and 33%). The SADs increased the accuracy of the estimates by reducing the constant and systematic errors, and the tendency to overestimate the actual severity, limited the number of evaluators who presented this trend, in addition to increasing the bias correction factor. The inexperienced evaluators were the ones that benefited the most from the SADs use. Once the SADs was introduced, 80% and 100% evaluators gave estimates free from constant and systematic errors, respectively. The improvement in precision was verified by the increase in the coefficient of determination and Lin's concordance correlation coefficient, by reducing absolute errors and increasing the reproducibility of the estimates.

RESUMO: O objetivo deste estudo foi desenvolver e validar uma escala diagramática para melhorar a acurácia, precisão e reprodutibilidade na avaliação da severidade da verrugose em folhas trilobadas do maracujazeiro azedo. A escala apresentou seis níveis de severidade (1; 3; 6; 11; 21 e 33%) e aumentou a acurácia das estimativas, reduzindo os erros constantes e sistemáticos, a tendência de superestimação em relação aos valores de severidade real e o número de avaliadores que apresentavam essa tendência, além de aumentar o fator de correção do desvio. Os avaliadores inexperientes foram os mais beneficiados pela utilização da escala, sendo que 80% e 100% destes avaliadores apresentaram estimativas livres de erros constantes e sistemáticos, respectivamente, quando a escala foi empregada. O aumento da precisão foi verificado pelo incremento dos coeficientes de determinação e de concordância de Lin, redução dos erros absolutos e aumento da reprodutibilidade das estimativas.

Development and validation of a standard area diagram set as assessment aid for estimating the severity of bacterial spot on tri-lobed leaves of yellow passion fruit / Desenvolvimento e validação de escala diagramática como auxílio na avaliação da severidade da bacteriose em folhas trilobadas do maracujazeiro azedo

Bacterial spot (Xanthomonas axonopodis pv. passiflorae) significantly reduces yellow passion fruit (Passiflora edulis Sims) yield and longevity. A standard area diagram set (SADs) for severity assessment of bacterial spot on tri-lobed leaves of yellow passion was developed and validated in this study. The SADs consisted of eight severity levels (2; 4; 9; 18; 35; 58; 80; and 94%). For its validation, 20 raters, who initially estimated the disease severity without the aid of the SADs, were divided into four groups (G1 and G3, inexperienced; G2 and G4, experienced). Subsequently, G1 and G2 performed the second evaluation without the SADs, and G3 and G4 completed the second evaluation with the proposed SADs. The accuracy and precision of the assessments were determined by simple linear regression and by the Lin's concordance correlation coefficient (LCCC). The proposed SADs allowed accurate and precise quantification of bacterial spot severity, increasing the agreement between estimated and actual values. Inexperienced raters benefited the most from the use of the SADs. The increase in accuracy and precision in the non-aided groups, when present, was less pronounced than those increments observed in the SADs-aided groups. The LCCC confirmed the increases in accuracy and precision detected by the linear regression analysis.

A bacteriose (Xanthomonas axonopodis pv. passiflorae) reduz significativamente a produção e longevidade do maracujazeiro azedo (Passiflora edulis Sims). Uma escala diagramática para a avaliação da severidade da bacteriose em folhas trilobadas do maracujazeiro azedo foi desenvolvida e validada neste estudo. A escala diagramática apresentou oito níveis de severidade (2; 4; 9; 18; 35; 58; 80 e 94%). Para a sua validação, os 20 avaliadores foram divididos em quatro grupos (G1 e G3, sem experiência; G2 e G4, com experiência), que inicialmente estimaram a severidade da doença sem auxílio da escala. Posteriormente, G1 e G2 fizeram outra avaliação sem escala, e G3 e G4 realizaram a avaliação com a escala proposta. A acurácia e a precisão das estimativas foram determinadas por regressão linear simples e pelo coeficiente de correlação de concordância de Lin (LCCC). A escala diagramática proposta permitiu quantificar a severidade da bacteriose de forma acurada e precisa, aumentando a concordância entre os valores estimados e os reais. Os avaliadores inexperientes foram os mais beneficiados pelo uso da escala. O aumento da acurácia e precisão nos grupos que realizaram dupla avaliação sem escala, quando ocorreu, foi mais discreto que os incrementos observados nos grupos que utilizaram a escala. O LCCC confirmou os incrementos da acurácia e precisão detectados pela análise de regressão linear.

A diagramatic scale to quantify severity of antracnose in Rubus glaucus Benth / Uma escala diagramática para quantificar a severidade da antracnose em Rubus glaucus Benth

ABSTRACT: Rubus glaucus Benth, commonly referred to as mora de Castilla, is affected by Colletotrichum acutatum, as it induces anthracnose in many of the plant organs. Generally, it affects the fruits during the post-harvest phase and damages them, causing economic losses due to the poor crop quality. At present, no standardized methods are available for this pathosystem that can be used to characterize quantitatively the epidemic and to permit the prediction and comparison of the disease management techniques. In this research, we proposed a logarithmic diagrammatic scale of the severity of anthracnose induced by C. acutatum in the fruits of the thornless variety of R. glaucus Benth. This scale is constructed on the adjustment of the Weber-Fechner law and includes six classes, viz., 0%, 1-6%, 7-25%, 26-50%, 51-75%, 76-100%. The scale was validated using 14 evaluators, which entailed measuring the affected fruits with and without utilizing the scale; this improved the precision, accuracy and reproducibility of the calculations whenever the scale was used. We concluded that the scale proposed can be used to assess the severity of anthracnose induced by the fungus in the R. glaucus Benth fruits.

RESUMO: Mora de Castilla (Rubus glaucus Benth) é afetado por Colletotrichum acutatum, causando antracnose em órgãos diferentes da planta. Nos frutos geralmente é em pós-colheita, causando danos que geram perdas econômicas relacionadas com a qualidade das culturas. Ainda não existem para esse patossistema métodos padronizados para caracterizar quantitativamente a epidemia e que pode prever e comparar os métodos de manejo da doença. Por esta razão, neste trabalho foi criada uma escala logarítmica diagramática da severidade da antracnose causada pelo fungo C. acutatum em frutos de R. glaucus Benth com base na lei de Weber-Fechnere composto por 6 niveis: 0%, 1-6%, 7-25%, 26-50%, 51-75% e 76-100%. A escala foi validada por 14 evaluadores, fazendo medições de frutos afetados com e sem o uso da escala, que mostrou melhor precisão, exatitude e reproducibilidade nas avaliações em que o uso da escala foi feito. Isto permite concluir que a escala proposta pode ser usada na estimação da severidade da antracnose causada em frutos de R. glaucus Benth.

Image-based Analysis to Study Plant Infection with Human Pathogens.

Our growing awareness that contaminated plants, fresh fruits and vegetables are responsible for a significant proportion of food poisoning with pathogenic microorganisms indorses the demand to understand the interactions between plants and human pathogens. Today we understand that those pathogens do not merely survive on or within plants, they actively infect plant organisms by suppressing their immune system. Studies on the infection process and disease development used mainly physiological, genetic, and molecular approaches, and image-based analysis provides yet another method for this toolbox. Employed as an observational tool, it bears the potential for objective and high throughput approaches, and together with other methods it will be very likely a part of data fusion approaches in the near future.

Association of Olpidium bornovanus and Melon necrotic spot virus with Vine Decline of Melon in Guatemala.

Thirty-one soil samples from 14 different fields of Guatemala melon with vine decline symptoms were analyzed for the presence of organisms associated with the disease. With a soil-dilution plating method, only Macrophomina phaseolina was detected in five samples. With a melon bait plant technique, Olpidium bornovanus, often together with Melon necrotic spot virus (MNSV), was found in nearly all the samples, corresponding with all the fields studied. Other pathogens that were detected less frequently included Pythium aphanidermatum, Monosporascus cannonballus, and Rhizoctonia solani. Consequently, O. bornovanus and MNSV were uniquely associated with disease occurrence and thus are the most probable cause of melon vine decline in the fields studied.