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Revista mexicana de fitopatología

versión On-line ISSN 2007-8080versión impresa ISSN 0185-3309

Rev. mex. fitopatol vol.41 no.3 Texcoco sep. 2023  Epub 13-Oct-2023

https://doi.org/10.18781/r.mex.fit.2302-9 

Phytopathological notes

Diagrammatic scale to evaluate the severity of gray mold (Botrytis cinerea) in pomegranate

Alberto Patricio-Hernández1 

Yuridia Mercado-Flores*  1 

Alejandro Téllez-Jurado1 

María del Rocío Ramírez-Vargas1 

Andrés Quezada-Salinas2 

1 Universidad Politécnica de Pachuca, Carretera Pachuca-Cd. Sahagún, Km 20, Rancho Luna, Ex Hacienda de Santa Bárbara, C.P. 43830. Zempoala, Hidalgo, México;

2 Centro Nacional de Referencia Fitosanitaria, Servicio Nacional de Sanidad, Inocuidad y Calidad Agroalimentaria, Carretera Federal México-Pachuca, Km 37.5, Avenida Centenario de la Educación, Colonia Santa Ana, C.P. 55740, Tecámac, Estado de México, México.


Abstract.

The aim of this study was to design and validate a diagrammatic scale to estimate the severity of gray mold induced by Botrytis cinerea in pomegranate cultivation. A total of 120 healthy and diseased fruits with varying degrees of affliction were collected from orchards with active production located in the municipalities of Chilcuahutla and Taxquillo in the state of Hidalgo, Mexico (20° 18’ 11’’ N, 99° 14’ 23’’ W, 20° 32’ 01’’ N, 99° 20’ 03’’ W, respectively). From these, 60 were selected to determine the severity percentage, according to a 6-class scale (Class 0 = 0%, Class 1 = >0% - 5% - 10%, Class 2 = >10% - 25% - 50%, Class 3 = >50% - 75% - 85%, Class 4 = >85% - 90% - 95%, and Class 5 = >95% - 100%), using the 2LOG software. With the obtained data, representative images were selected to build the diagrammatic scale using Adobe Photoshop. The accuracy (r2), precision (β0), and reproducibility (β1) were verified by simple linear regression applied to the data obtained by 12 evaluators with and without experience in the observation of plant diseases. As a result, values of r2 of 0.42 and 0.85 were obtained, without and with the use of the scale, respectively, which confirmed that this tool is suitable to evaluate the severity of the disease accurately and reproducibly.

Keywords: Phytosanitary; Punica granatum; Botrytis cinerea; disease measurement.

Resumen.

El objetivo del presente trabajo fue diseñar y validar una escala diagramática para estimar la severidad del moho gris inducida por Botrytis cinerea en el cultivo de granada. Se colectaron 120 frutos sanos y enfermos con diferentes grados de afectación de huertos con producción activa localizados en los municipios de Chilcuahutla y Taxquillo en el estado de Hidalgo, México (20° 18’ 11’’ N, 99° 14’ 23’’ O, 20° 32’ 01’’ N, 99° 20’ 03’’ O, respectivamente), de los cuales, se seleccionaron 60 para determinar el porcentaje de severidad, de acuerdo a una escala de 6 clases (Clase 0= 0%, Clase 1 = >0% - 5% - 10%, Clase 2 = >10% - 25% - 50%, Clase 3 = >50% - 75% - 85%, Clase 4 = >85% - 90% - 95% y Clase 5 = >95% - 100%) mediante el software 2LOG. Con los datos obtenidos se seleccionaron imágenes representativas para construir la escala diagramática mediante Adobe Photoshop. Se verificó la exactitud (r2), la precisión (β 0) y la reproducibilidad (β 1) mediante regresión lineal simple aplicada a los datos obtenidos por 12 evaluadores con y sin experiencia en la observación de enfermedades en plantas. Como resultado se obtuvieron valores de r2 de 0.44 sin el uso de la escala, y con el uso de esta herramienta de 0.81 y 0.90 para la primera y segunda evaluación respectivamente, lo cual confirmó que esta herramienta es adecuada para evaluar la severidad de la enfermedad de manera precisa y reproducible.

Palabras clave: Fitosanidad; Punica granatum; Botrytis cinerea; medición de enfermedad.

Pomegranate is the fruit of the pomegranate tree (Punica granatum), which is consumed worldwide and is currently cultivated in Iran, Spain, Italy, Afghanistan, the United States, India, China, Russia, Uzbekistan, Morocco, Greece and Mexico (Koba and Yanagita, 2011). Its production has gained importance due to the functional properties it possesses, which is why various food products such as juices and liquors are produced, in addition to its importance in the cosmetic industry (Ge et al., 2021). In Mexico in 2021, 1,251 ha were cultivated and 8,636 t were produced. The states with the highest harvest volumes were Morelos, Hidalgo and Oaxaca with 1,622, 1,467 and 1,327 t, respectively (SIAP, 2021), destined for both domestic consumption and export. Pomegranate orchards are affected by diseases induced by various microorganisms such as Alternaria spp. and Aspergillus spp., with the greatest impact being those that directly affect the fruit pre-harvest (Behzad et al., 2020). One such disease is gray mold induced by Botrytis cinerea, which has been reported mainly in pomegranate orchards in Greece and Pakistan (Bardas et al., 2009; Alam et al., 2018). It occurs after flowering at the beginning of fruit formation and is characterized by the presence of spots that increase in size, with light to dark brown expanded lesions of soft consistency, followed by the appearance of gray mycelium on infected surfaces. Fruit may remain mummified on the tree. Recently, this phytosanitary problem has been reported in the State of Mexico, Mexico (Patricio-Hernández et al., 2023). Diagrammatic scales could be a useful tool to estimate the severity of gray mold in pomegranate fruits pre- and post-harvest. These tools allow correct interpretation of disease advancement and progress in crops, defined as sets of illustrations of plants or plant organs, with signs and symptoms that show the percentages of area affected by the disease. This is based on the Weber-Fechner principle, which establishes classes in a logarithmic system that eliminates arbitrary designation of severity levels (French and Hebert, 1980). The scales should be quick and simple when used under field and post-harvest conditions, as well as accurate, precise and reproducible (Richard et al., 2021; Vereschuk et al., 2022). To date, no scales for assessing the severity of gray mold on pomegranate fruits have been reported. The objective of the present study was to develop and validate a diagrammatic scale to help growers and technicians assess disease severity.

During the months of July to September 2022, 120 pomegranate fruits with and without symptoms of gray mold (Botrytis cinerea) were collected in active production plots located in the municipalities of Chilcuahutla and Taxquillo, Hidalgo, Mexico (20° 18’ 11’’ N, 99° 14’ 23’’ W, 20° 32’ 01’’ N, 99° 20’ 03’’ W, respectively). Subsequently, 60 fruits representative of the different degrees of damage were selected. To obtain the actual severity, each fruit was divided in half in order to photograph the total surface of each one using a Canon T7 camera (Verechuk et al., 2022).

To eliminate the background, the images were processed with GIMP® v.2.10.12 software. Quantification of the total and affected area was performed using Image Tool v1.8.0. With the obtained data, the actual severity percentage was calculated using the following formula: severity = (diseased area/total image area) * 100 (Nutter Jr et al., 2006; Ortega-Acosta et al., 2016). The data were used to define the minimum and maximum values of actual severity, which were then used to generate a logarithmic scale with six classes, using the 2LOG v.1 software (Mora-Aguilera and Acevedo-Sánchez, 2018). This follows the Weber-Fechner visual acuity law (Horsfall and Cowling, 1978). The obtained data were used to construct the diagrammatic scale with Adobe Photoshop software (Fantin et al., 2018).

To validate the diagrammatic scale, 60 digital images representative of different degrees of severity were randomly inserted into individual slides to be visualized in Microsoft 365® PowerPoint and presented to 18 evaluators with and without experience in observing plant diseases. They carried out independent evaluations with approximately 20 s per image for visualization. Data from this first evaluation were expressed as percentage of severity (Fragoso-Benhumea et al., 2022). For the first and second evaluations using the scale, 12 evaluators were selected based on the number of correct scores in the evaluation without the scale and their willingness for subsequent participation (Belan et al., 2014). Each evaluation was carried out with an interval of 7 days between them.

To quantify the accuracy of the severity evaluations made by the evaluators, a simple linear regression was performed to verify the following hypotheses: for the intercept (β 0) the null hypothesis H0: β 0=0 versus H1: β 0≠0 and for the slope coefficient (β 1) H0: β 1=1 versus H1: β 1≠1, with a significance level of 5%, using a t-test. The actual values obtained were used as the independent variable and the estimated values per evaluator were used as the dependent variable (Da silva et al., 2019). This took into account that if the estimated values of the slope differ from 0, they indicate overestimation of the real severity when β 0 >0 and underestimation if β 0<0. Similarly, if the slope data differ from 1, they indicate overestimation of disease (>1) or underestimation (<1) at all disease severity levels (Nutter Jr. and Schultz, et al., 1995; Nutter et al., 2006; Ortega-Acosta et al., 2016).

Additionally, the precision of the estimation was determined by the coefficient of determination (r2) of the linear regression and the absolute error was plotted. Furthermore, a paired data analysis per evaluator was performed. Statistical analyses were conducted using the Rstudio program (http://www.rstudio.com/).

From field collections in the municipalities of Chilcuautla and Taxquillo, Hidalgo, 120 fruits were obtained, of which 60 were selected based on their actual degree of severity. Those with 0% severity were considered healthy, while those showing signs and symptoms of gray mold were characterized by the presence of brown lesions originating at the base of the calyx and advancing towards the peduncle, causing rotting of the infected area with values ranging from 5 to 100%.

Based on the percentages of damaged area of the 60 selected fruits, the 2LOG program allowed the definition of six severity classes. The ranges and midpoints of each class (0, 1, 2, 3, 4 and 5) were expressed as percentage of affected area: Class 0= 0%, Class 1 = (>1 - 5 - 10)%, Class 2 = (>11 - 25 - 50)%, Class 3 = (>51 - 75 - 85)%, Class 4 = (>86 - 90 - 95)% and Class 5 = (>96 - 100)% (Figure 1).

Figure 1 TableDiagrammatic scale for evaluation of gray mold (Botrytis cinerea) severity on pomegranate (Punica granatum) fruit. Severity intervals for each class are shown in parentheses. 

The accuracy of the evaluations showed significant differences with and without the use of the designed scale. When the scale was not used, the r2 values ranged from 0.06 to 0.87 with a mean of 0.44. However, with the use of the scale, the results were from 0.71 to 0.93 for the first evaluation and from 0.70 to 0.97 for the second evaluation, with mean values of 0.81 and 0.90, respectively. Therefore, the estimations were accurate (Table 1).

Table 1 Intercept (β0), slope (β1) and coefficient of determination (r2) of the linear regression equation of visual estimates of gray mold severity in Punica granatum fruits, performed with and without diagrammatic scaling. 

Coeficientes
Con escala
Sin Escala Primera Evaluación Segunda Evaluación
β0 β1 r2 β0 β1 r2 β0 β1 r2
EV1 11.96 ns 0.97 ns 0.68 0.05 ns 1.00 ns 0.93 0.25 * 0.93 ns 0.82
EV2 6.47 * 0.43 ns 0.37 0.10 ns 0.82 ns 0.72 0.09 ns 0.99 ns 0.91
EV3 20.85 ns 0.67 ns 0.32 0.25 * 0.89 ns 0.84 0.03 ns 1.04 ns 0.94
EV4 18.81 ns 0.69 ns 0.28 0.24 ns 1.83 ns 0.72 -0.03 ns 1.01 ns 0.94
EV5 4.06 ns 0.88 ns 0.61 0.11 ns 1.02 ns 0.86 0.00 ns 1.10 ns 0.86
EV6 13.04 ns 0.59 ns 0.36 0.11 ns 1.05 ns 0.78 0.03 ns 1.01 ns 0.96
EV7 12.27 ns 0.81 ns 0.68 0.09 ns 0.91 ns 0.77 0.27 * 0.88 ns 0.85
EV8 9.92 * 0.77 ns 0.54 0.14 ns 0.96 ns 0.85 -0.04 ns 1.03 ns 0.96
EV9 16.15 ns 0.38 ns 0.20 0.07 ns 0.96 ns 0.89 0.76 ns 0.96 ns 0.88
EV10 54.63 ns 0.29 * 0.06 0.09 ns 1.01 ns 0.75 0.04 ns 0.99 ns 0.97
EV11 -1.65 ns 0.95 ns 0.87 0.15 ns 0.94 ns 0.71 0.16 ns 0.94 ns 0.70
EV12 14.13 ns 0.56 ns 0.33 -0.05 ns 1.00 ns 0.86 0.03 ns 1.01 ns 0.96
0.44 0.81 0.90

* Means that the null hypotheses for the intercept (H0: β 0=0) and slope (Ho: β 1=1) were rejected by t-test (P=0.05). ns= Not significant. EV= Evaluator.

Regarding the linear regression results, in the evaluation where the scale was not used, the intercept values were greater than one, indicating overestimation of severity by most evaluators. In the case of the slope values, for evaluator 10 (EV10) it was significantly different from 1, however, there was a tendency toward underestimation, with the exception of EV1 and EV11 that showed values closer to 1 (Table 1).

In the initial evaluation employing the scale, the intercept values showed a tendency to overstate disease severity. Specifically, EV3’s intercept significantly deviated from 0. As for the slope values, EV4, EV5, EV6 and EV10 showed overestimation compared to the other evaluators. In the second evaluation, EV4 and EV5 demonstrated an underestimation of severity, as reflected by values exceeding 1. Meanwhile, EV1 and EV7 yielded statistically distinct values from 0. Concerning the slope, none of the data exhibited significant differences, although their values closely approximated 1 (Table 1).

In general, concentrating on the evaluations conducted with the scale and considering the null hypotheses (H0: β 0=0 and H0: β 1=1), it is observable that β 0 maintained proximity to 0 across all evaluators. Likewise, β 1 uniformly hovered around 1. This confirms that using the diagrammatic scale of gray mold severity allows obtaining values of precision and accuracy close to those of real severity, even when there are slight tendencies of underestimation and overestimation. This statement is reinforced when comparing the absolute error values of the evaluations, where a decrease in absolute error is observed when using the designed scale (Figure 2).

Figure 2 Graphical representation of the absolute error of the estimates of gray mold severity in pomegranate fruits. a) Evaluation carried out without support of the diagrammatic scale, b) and c) Evaluations carried out with support of the diagrammatic scale, d) and e) Representation of b) and c) at a smaller scale of absolute error.  

The combinations of the r2 values of the evaluations showed that the scales are reproducible. Where the diagrammatic scale was not used, an interval of 0.13 to 0.77, with a mean of 0.44, was obtained. With the scale, the r2 intervals were 0.72 to 0.91, and 0.76 to 0.97, in the first and second evaluations, respectively, with an overall mean value of 0.85 (Table 2).

Table 2 Coefficient of determination (r2) of linear regression equations relating paired evaluator estimates of gray mold severity caused by B. cinerea on pomegranate fruit. Comparisons are made between evaluations done without use of the scale, versus the first and second evaluations where the scale was used. 

Evaluación sin escala EV2 EV3 EV4 EV5 EV6 EV7 EV8 EV9 EV10 EV11 EV12
EV1 0.52 0.50 0.48 0.64 0.52 0.68 0.61 0.44 0.37 0.77 0.50
EV2 0.34 0.32 0.49 0.36 0.52 0.45 0.28 0.21 0.62 0.35
EV3 0.30 0.46 0.34 0.50 0.43 0.26 0.19 0.59 0.32
EV4 0.45 0.32 0.48 0.41 0.24 0.17 0.57 0.30
EV5 0.49 0.64 0.57 0.40 0.33 0.74 0.47
EV6 0.52 0.45 0.28 0.21 0.62 0.35
EV7 0.61 0.44 0.37 0.77 0.50
EV8 0.37 0.30 0.70 0.43
EV9 0.13 0.53 0.26
EV10 0.46 0.19
EV11 0.60
Primera evaluación con escala
EV1 0.83 0.89 0.83 0.90 0.86 0.85 0.89 0.91 0.84 0.82 0.90
EV2 0.78 0.72 0.79 0.75 0.75 0.78 0.80 0.74 0.72 0.79
EV3 0.78 0.85 0.81 0.81 0.84 0.87 0.80 0.78 0.85
EV4 0.79 0.75 0.75 0.78 0.80 0.74 0.72 0.79
EV5 0.82 0.82 0.85 0.87 0.81 0.79 0.86
EV6 0.78 0.81 0.83 0.77 0.75 0.82
EV7 0.81 0.83 0.76 0.74 0.82
EV8 0.87 0.80 0.78 0.85
EV9 0.82 0.80 0.87
EV10 0.73 0.81
EV11 0.79
Segunda evaluación con escala
EV1 0.87 0.88 0.88 0.84 0.89 0.84 0.89 0.85 0.90 0.76 0.89
EV2 0.93 0.93 0.89 0.94 0.88 0.94 0.90 0.94 0.81 0.94
EV3 0.94 0.90 0.95 0.90 0.95 0.91 0.96 0.82 0.95
EV4 0.90 0.95 0.90 0.95 0.91 0.96 0.82 0.95
EV5 0.91 0.86 0.91 0.87 0.92 0.78 0.91
EV6 0.91 0.96 0.92 0.97 0.83 0.96
EV7 0.91 0.87 0.91 0.78 0.91
EV8 0.92 0.97 0.83 0.96
EV9 0.93 0.79 0.92
EV10 0.84 0.97
EV11 0.83

EV= Evaluator. / EV= Evaluador.

The use of diagrammatic scales is efficient in evaluating disease severity in plants (Fantin et al., 2018). Recently, the presence of gray mold caused by B. cinerea on pomegranate fruits in Mexico was reported (Patricio-Hernández et al., 2023), and to our knowledge, a diagrammatic scale for evaluating the severity of this disease has not been officially reported. The scale developed in the present investigation allows reliable evaluation of the severity of this disease with greater precision and accuracy. When the scale was not used, the average r2 value was 0.44, while in the first and second evaluations with the scale, averages of 0.81 and 0.90 were obtained, respectively. This represents a significant increase, agreeing with what was observed by Belan et al. (2014), who obtained r2 values of 0.89 and 0.87 in the first and second evaluations, respectively, when using their designed scale for coffee tree leaf spot.

The r2 values of the present investigation were significantly higher in the evaluations where the scale was used. This is similar to those reported by Fragoso-Benhumea et al. (2022), who obtained values of 0.90 to 0.97, with a mean of 0.93 when evaluating the severity of rust (Uromyces viciae-fabae) in the broad bean crop, with and without the use of diagrammatic scales. They concluded that this value improves with the use of diagrammatic scales. This indicates that the designed scale can be used in the field, since it has precision values (r2) close to 1 in the evaluations.

Several studies have shown a tendency to overestimate (Figueiredo et al., 2022; Pereira et al., 2021) and to a lesser extent underestimate (Braga et al., 2020) when diagrammatic scales are not used. In the present work, overestimates were observed in most of the absolute data when the diagrammatic scale was not used, in contrast to the evaluations where it was used. This behavior may be due to visual stimuli, such as similar colorations in the lesions that are not considered for the evaluation of severity, as reported by Perina et al. (2019). They identified factors that can lead to overestimation of the severity of brown spot on leaves of Citrus reticulata caused by Alternaria sp. due to the presence of different pigments on the leaf surface that do not correspond to the evaluated disease. This can affect both experienced and inexperienced evaluators.

The use of the scale allowed a considerable decrease in the absolute error of the evaluations, compared to when it was not used (without the scale it was from -59 to 39%, with the scale it was from -0.4 to 0.4% and -0.16 to 0.48% in the first and second evaluations, respectively). Similar results were obtained by Muños-Arias et al. (2020) for gray mold on Rubus glaucus, where this value decreased with use of the diagrammatic scale (from -30 to 30% without the scale to -20 to 20% with the scale). On the other hand, Ortega-Acosta et al. (2016) and Nutter Jr and Schultz (1995) mention that absolute error values less than 5% are considered acceptable. In this work, results of -0.35 to 0.5% were obtained on average for the two evaluations, which supports the accuracy of the evaluations when using the scale. Thus, the present research provides a reliable instrument for evaluating the severity induced by gray mold in pomegranate fruits.

When r2 values among evaluators were compared, it was evident that the designed scale exhibited precision, evident in its capacity to narrow the variation intervals within comparisons when employing the diagrammatic scale. This particular methodology enabled the accurate, precise, and reproducible estimation of gray mold severity attributed to B. cinerea on pomegranate fruits. As a result, the scale holds the potential to serve as an effective tool for disease management, monitoring, and surveillance purposes.

Acknowledgments

The authors would like to thank the Consejo Nacional de Humanidades, Ciencias y Tecnologías (CONAHCyT) for the grant awarded to Alberto Patricio Hernández, and the participants who served as evaluators for this work.

Cited literature

Alam MW, Rehman A, Ahmad S, Sarwar M, Naseem MK, Chattha MB, Malik AU and Ali S. 2018. First report of Botrytis cinerea causing postharvest fruit rot on stored pomegranates in Pakistan. Plant Disease 103:374-374. https://doi.org/10.1094/PDIS-06-18-1114-PDN [ Links ]

Bardas GA, Tzelepis GD, Lotos and Karaoglanidis GS. 2009. First report of Botrytis cinerea causing gray mold of pomegranate (Punica granatum) in Greece. Plant Disease 93:1346-1346. https://doi.org/10.1094/PDIS-93-12-1346C [ Links ]

Behzad N, Seyed-Saeid S and Shahin R. 2020. Quality detection of pomegranate fruit infected with fungal disease. International Journal of Food Properties 23:9-21. https://doi.org/10.1080/10942912.2019.1705851 [ Links ]

Belan LL, Pozza EA, Freitas MLO, Souza RM, Jesús Junior WC and Oliveira JM. 2014. Diagrammatic scale for assessment of bacterial blight in coffee leaves. Journal of Phytopathology 162:801-810. http://dx.doi.org/10.1111/jph.12272 [ Links ]

Braga K, Fantin LH, Roy JMT, Canteri MG and Paiva AM. 2020. Development and validation of a diagrammatic scale for the assessment of the severity of bacterial leaf streak of corn. European Journal of Plant Pathology 157:367-375. https://doi.org/10.1007/s10658-020-02008-7 [ Links ]

Da silva GCBM, Pio R, Pereira RCM, Peche PM and Pozza EA. 2019. Development and validation of a severity scale for assessment of fig rust. Phytopathologia Mediterranea 58:597-605. http://dx.doi.org/10.14601/Phyto-10967 [ Links ]

Fantin LH, Braga K, Canteri MG and Borges EP. 2018. Development and validation of diagrammatic scale to assess target spot severity in cotton. Australasian Plant Pathology 47:491-497. https://doi.org/10.1007/s13313-018-0576-6 [ Links ]

Figueiredo Y, Oliveira JM, Almeida KA, Pereira PF, Pedroso LA, Guimaraes MRF, Moreira-Costa M and Ampélio-Pozza E. 2022. Coffee leaf rust assessment: comparison and validation of diagrammatic scales for Coffea arabica. European Journal of Plant Pathology 164:411-427. https://doi.org/10.1007/s10658-022-02570-2 [ Links ]

Fragoso-Benhumea JM, Sánchez-Pale JR, Castañeda-Vildózola A, Franco-Mora O, Gutiérrez-Ibáñez AT, Contreras-Rendón A and García-Velasco R. 2022. Diagrammatic scale for rust severity assessment in broad bean (Vicia faba). Mexican Journal of Phytopathology 40(3): 474-482. https://doi.org/10.18781/R.MEX.FIT.2206-2 [ Links ]

French E y Hebert T. 1980. Métodos de investigación fitopatológica. IICA, San José Costa Rica, p.289. [ Links ]

Ge S, Dou L, Wang J, Zhula G, Yang J, Li Z and Tu Y. 2021. A unique understanding of traditional medicine of pomegranate, Punica granatum L. and its current research status. Journal of Ethnopharmacology 271:113877. https://doi.org/10.1016/j.jep.2021.113877. [ Links ]

Horsfall JG and Cowling EB. 1978. Pathometry: the measurement of plant disease Pp:119-136. In: Horsfall JG and Cowling EB (eds.). London UK. How disease develops in populations. Elsevier. London UK. 407p. [ Links ]

Koba K and Yanagita. 2011. Potential health benefits of pomegranate (Punica granatum) seed oil containing conjugated linolenic acid. Pp:919-924. In: Nuts and Seeds in Health and Disease Prevention. Academic Press. United States of America. 2607p. https://doi.org/10.1016/B978-0-12-375688-6.10108-2 [ Links ]

Mora-Aguilera G and Acevedo-Sánchez G. 2018. DOSLOG 2.0v. Laboratorio de análisis de riesgo epidemiológico fitosanitario (CP -LANREF). Montecillo, Texcoco, México [ Links ]

Muños-Arias S, Guerrero-Álvarez GE and González-Patiño PA. 2020. Diagrammatic scale for measuring severity of gray mould in thornless Castilla blackberry (Rubus glaucus Benth). Ciencia Rural 50:1678-4596. http://doi.org/10.1590/0103-8478cr20190859 [ Links ]

Nutter Jr. FW, Esker PD and Coelho-Netto RA. 2006. Disease assessment concepts and the advancements made in improving the accuracy and precision of plant disease data. European Journal of Plant Pathology 115:95-103. http://dx.doi.org/10.1007/s10658-005-1230-z [ Links ]

Nutter FW and Schultz PM. 1995. Improving the accuracy and precision of disease assessments: selection of methods and use of computer-aided training programs. Canadian Journal of Plant Pathology 17:174-184. [ Links ]

Ortega-Acosta SA, Velasco-Cruz C, Hernández-Morales J, Ochoa-Martínez DL and Hernández-Ruiz J. 2016. Diagrammatic logarithmic scales for assess the severity of spotted leaves and calyces of roselle. Mexican Journal of Phytopathology 34:270-285. https://doi.org/10.18781/R.MEX.FIT.1606-6 [ Links ]

Patricio-Hernández A, Moreno-Velázquez M, Quezada-Salinas A and Mercado-Flores Y. 2023. First report of Botrytis cinerea causing gray mold of pomegranate (Punica granatum L.) in Mexico. Journal of Plant Diseases and Protection. https://doi.org/10.1007/s41348-023-00715-x [ Links ]

Pereira RCM, de Oliveira LM, Tassone GAT, Rego GMS and Poza EA. 2021. Diagrammatic scale for phyllachora in Australian red cedar. Australasian Plant Pathology 50:81-90. https://doi.org/10.1007/s13313-020-00749-x [ Links ]

Perina FJ, Belan LL, Moreira SI, Nery EM, Alves E and Posa EA. 2019. Diagrammatic scale for assessment of Alternaria brown spot severity on tangerine leaves. Journal of Plant Pathology 101:981-990. https://doi.org/10.1007/s42161-019-00306-6 [ Links ]

Richard B, Qi A and Fitt B. 2021. Control of crop diseases through Integrated Crop Management to deliver climate-smart farming systems for low- and high-input crop production. Plant Pathology 71:187-206. https://doi.org/10.1111/ppa.13493 [ Links ]

Servicio de Información Agroalimentaria y Pesquera (SIAP). 2021. Estadística de Producción Agrícola. Sistema de Información Agrícola y Pesquera. http://infosiap.siap.gob.mx/gobmx/datosAbiertos_a.php (Consulta, septiembre 2021). [ Links ]

Vereschuk ML, Dominguez FG, Alvarenga AE and Zapata PD. 2022. Diagrammatic scale for quantification of severity of white thread blight disease in yerba mate (Ilex paraguariensis Saint Hilaire). Crop Science 94:e20201931. https://doi.org/10.1590/0001-3765202220201931 [ Links ]

Received: February 26, 2023; Accepted: August 25, 2023

* Corresponding author: yuridiamercado@upp.edu.mx

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