A disease predictive model based on epidemiological factors for the management of bacterial leaf blight of rice

Abstract Rice is a widely consumed staple food for a large part of the worlds human population. Approximately 90% of the worlds rice is grown in Asian continent and constitutes a staple food for 2.7 billion people worldwide. Bacterial leaf blight (BLB) caused by Xanthomonas oryzae pv. oryzae is one of the devastating diseases of rice. A field experiment was conducted during the year 2016 and 2017 to investigate the influence of different meteorological parameters on BLB development as well as the computation of a predictive model to forecast the disease well ahead of its appearance in the field. The seasonal dataset of disease incidence and environmental factors was used to assess five rice varieties/ cultivars (Basmati-2000, KSK-434, KSK-133, Super Basmati, and IRRI-9). The accumulated effect of two year environmental data; maximum and minimum temperature, relative humidity, wind speed, and rainfall, was studied and correlated with disease incidence. Average temperature (maximum & minimum) showed a negative significant correlation with BLB disease and all other variables; relative humidity, rainfall, and wind speed had a positive correlation with BLB disease development on individual varieties. Stepwise regression analysis was performed to indicate potentially useful predictor variables and to rule out incompetent parameters. Environmental data from the growing seasons of July to October 2016 and 2017 revealed that, with the exception of the lowest temperature, all environmental factors contributed to disease development throughout the cropping season. A disease prediction multiple regression model was developed based on two-year data (Y = 214.3-3.691 Max T-0.508 Min T + 0.767 RH + 2.521 RF + 5.740 WS), which explained 95% variability. This disease prediction model will not only help farmers in early detection and timely management of bacterial leaf blight disease of rice but may also help reduce input costs and improve product quality and quantity. The model will be both farmer and environmentally friendly.

Resumo O arroz é um alimento básico amplamente consumido por grande parte da população humana mundial. Aproximadamente 90% do arroz do mundo é cultivado no continente asiático e constitui um alimento básico para 2,7 bilhões de pessoas em todo o mundo. O crestamento bacteriano das folhas (BLB) causado por Xanthomonas oryzae pv. oryzae é uma das doenças devastadoras do arroz. Um experimento de campo foi realizado durante os anos de 2016 e 2017 para investigar a influência de diferentes parâmetros meteorológicos no desenvolvimento do BLB, bem como o cálculo de um modelo preditivo para prever a doença bem antes de seu aparecimento em campo. O conjunto de dados sazonais de incidência de doenças e fatores ambientais foi usado para avaliar cinco variedades/cultivares de arroz (Basmati-2000, KSK-434, KSK-133, Super Basmati e IRRI-9). O efeito acumulado de dados ambientais de dois anos; temperatura máxima e mínima, umidade relativa do ar, velocidade do vento e precipitação pluviométrica foram estudados e correlacionados com a incidência da doença. A temperatura média (máxima e mínima) apresentou correlação significativa negativa com a doença BLB e todas as outras variáveis; umidade relativa, precipitação e velocidade do vento tiveram uma correlação positiva com o desenvolvimento da doença BLB em variedades individuais. A análise de regressão stepwise foi realizada para indicar variáveis preditoras potencialmente úteis e para descartar parâmetros incompetentes. Os dados ambientais das safras de julho a outubro de 2016 e 2017 revelaram que, com exceção da temperatura mais baixa, todos os fatores ambientais contribuíram para o desenvolvimento da doença ao longo da safra. Um modelo de regressão múltipla de previsão de doença foi desenvolvido com base em dados de dois anos (Y = 214,3-3,691 Max T-0,508 Min T + 0,767 RH + 2,521 RF + 5,740 WS), que explicou 95% de variabilidade. Este modelo de previsão de doenças não só ajudará os agricultores na detecção precoce e gestão atempada da doença bacteriana das folhas do arroz, mas também pode ajudar a reduzir os custos de insumos e melhorar a qualidade e a quantidade do produto. O modelo será agricultor e ambientalmente amigável.

A disease predictive model based on epidemiological factors for the management of bacterial leaf blight of rice / Um modelo preditivo de doenças baseado em fatores epidemiológicos para o manejo da queima bacteriana das folhas do arroz

Rice is a widely consumed staple food for a large part of the world's human population. Approximately 90% of the world's rice is grown in Asian continent and constitutes a staple food for 2.7 billion people worldwide. Bacterial leaf blight (BLB) caused by Xanthomonas oryzae pv. oryzae is one of the devastating diseases of rice. A field experiment was conducted during the year 2016 and 2017 to investigate the influence of different meteorological parameters on BLB development as well as the computation of a predictive model to forecast the disease well ahead of its appearance in the field. The seasonal dataset of disease incidence and environmental factors was used to assess five rice varieties/ cultivars (Basmati-2000, KSK-434, KSK-133, Super Basmati, and IRRI-9). The accumulated effect of two year environmental data; maximum and minimum temperature, relative humidity, wind speed, and rainfall, was studied and correlated with disease incidence. Average temperature (maximum & minimum) showed a negative significant correlation with BLB disease and all other variables; relative humidity, rainfall, and wind speed had a positive correlation with BLB disease development on individual varieties. Stepwise regression analysis was performed to indicate potentially useful predictor variables and to rule out incompetent parameters. Environmental data from the growing seasons of July to October 2016 and 2017 revealed that, with the exception of the lowest temperature, all environmental factors contributed to disease development throughout the cropping season. A disease prediction multiple regression model was developed based on two-year data (Y = 214.3-3.691 Max T-0.508 Min T + 0.767 RH + 2.521 RF + 5.740 WS), which explained 95% variability. This disease prediction model will not only help farmers in early detection and timely management of bacterial leaf blight disease of rice but may also help reduce input costs and improve product quality and quantity. The model will be both farmer and environmentally friendly.

O arroz é um alimento básico amplamente consumido por grande parte da população humana mundial. Aproximadamente 90% do arroz do mundo é cultivado no continente asiático e constitui um alimento básico para 2,7 bilhões de pessoas em todo o mundo. O crestamento bacteriano das folhas (BLB) causado por Xanthomonas oryzae pv. oryzae é uma das doenças devastadoras do arroz. Um experimento de campo foi realizado durante os anos de 2016 e 2017 para investigar a influência de diferentes parâmetros meteorológicos no desenvolvimento do BLB, bem como o cálculo de um modelo preditivo para prever a doença bem antes de seu aparecimento em campo. O conjunto de dados sazonais de incidência de doenças e fatores ambientais foi usado para avaliar cinco variedades/cultivares de arroz (Basmati-2000, KSK-434, KSK-133, Super Basmati e IRRI-9). O efeito acumulado de dados ambientais de dois anos; temperatura máxima e mínima, umidade relativa do ar, velocidade do vento e precipitação pluviométrica foram estudados e correlacionados com a incidência da doença. A temperatura média (máxima e mínima) apresentou correlação significativa negativa com a doença BLB e todas as outras variáveis; umidade relativa, precipitação e velocidade do vento tiveram uma correlação positiva com o desenvolvimento da doença BLB em variedades individuais. A análise de regressão stepwise foi realizada para indicar variáveis preditoras potencialmente úteis e para descartar parâmetros incompetentes. Os dados ambientais das safras de julho a outubro de 2016 e 2017 revelaram que, com exceção da temperatura mais baixa, todos os fatores ambientais contribuíram para o desenvolvimento da doença ao longo da safra. Um modelo de regressão múltipla de previsão de doença foi desenvolvido com base em dados de dois anos (Y = 214,3-3,691 Max T-0,508 Min T + 0,767 RH + 2,521 RF + 5,740 WS), que explicou 95% de variabilidade. Este modelo de previsão de doenças não só ajudará os agricultores na detecção precoce e gestão atempada da doença bacteriana das folhas do arroz, mas também pode ajudar a reduzir os custos de insumos e melhorar a qualidade e a quantidade do produto. O modelo será agricultor e ambientalmente amigável.

Identification of BLB resistant genes in some rice varieties for development of high yielding bacterial leaf blight tolerant types

Aim: To identify bacterial leaf blight resistant genes in some rice varieties so that these resistant varieties can be used as a good source of donor for BLB resistant genes in genetic enhancement program.Methodology: A total of sixty-one rice genotypes including resistant and susceptible checks were screened in field condition by artificial inoculation using IX020 strain of Xoo for two years (Kharif 2016 and 2017). These varieties were also genotyped for seven SSR markers tagged with major BLB resistant genes, i.e., Xa4, xa5, xa13 and Xa7. Results: In artificial screening, significant disease development was recorded and the varieties were categorized using disease scoring scale of IRRI, 1996 where seven cultivars exhibited resistance, while twenty-seven were found to be moderately resistant. In genotyping, there was distinct difference in banding position for resistant and susceptible genotypes. Genotypes having resistant disease reaction, carrying BLB resistant genes were identified. Interpretation: Genotypes IR-64, IR-68144-2b-2-2-3-1-127, Ratna, Surjamukhi, Kalinga-2, Azucena and Zheshan-2 expressed bands of RM markers closely linked to Xa4, xa5, xa13 and Xa7 BLB resistant genes and field testing also confirmed resistant host reaction against pathogens.

Clinical observation and analysis of BLB implant system over 10 years / 医学研究生学报

Objective The lack of observation on domestic BLB implant affect its longterm maintenance. The long-term clinical effect of domestic BLB implant system was evaluated by a 10-year follow-up.Methods A total of 179 implants were placed in 120 patients from January 2004 to December 2005 in Nanjing Stomatological Hospital. Patients accepted implant pattern of stage Ⅰ implantation and stage Ⅱ delayed exposure and prostheses were completed. Upper crowns were either screw-retained or cemented. Follow-up observation includes post-operation immediately, pre-secondary operation, 3 months and annually.Results Until December 2017, the rate of loss of follow-up was 6% and the overall survival rate was 95.2%. Implant failures were mainly due to the looseing of implant system caused by bone resorption and infection. Prosthetic complications include abutment loose, central screw loose, food impaction and porcelain fracture. There were no significant differences of failure cases comparing maxillary and mandible (P>0.05); neither comparing anterior teeth, pre-molars and molars (P>0.05)Conclusion When clinical indication is strictly controlled, BLB implant system is suitable for partially edentulous patients.

Screening of Aromatic Rice Cultivars for Bacterial Leaf Blight (BLB) Disease Resistance Gene Xa5 through Molecular Marker.

Bacterial leaf blight (BLB) caused by Xanthomonas oryzae pv. oryzae (Xoo) is one of the most common devastating diseases of rice (Oryza sativa) all around the world. Thus, present study has been conducted to screen 12 aromatic rice cultivars (Atashail, Basmati, Kalizira, Uknimodhu, Zira katari, BR5, BR14, Bina dhan9, BRRI dhan34, BRRI dhan37, BRRI dhan38 and BRRI dhan50) for BLB resistant gene xa5. The genotypes were analyzed using two genetic markers (RM 122 and RM 390) by Polymerase Chain Reaction (PCR). Where, BR 14 that was resistant to BLB was used as control. Both primers generated different banding patterns. Primer RM 122 produced 6 bands whereas primer RM 390 produced 10 bands, respectively. The highest level of gene diversity value (0.8889) was observed in locus RM 390 and the lowest level of gene diversity value (0.7361) was observed in locus RM122 with a mean diversity of 0.8125. The PIC values ranged from a low of 0.7007 (RM 122) to a high of 0.8785 (RM 390) with an average of 0.7896. Using the linked primer RM 122, the bands of xa5 gene were standardized by the amplified DNAs. The DNA band of 246 bp was considered as resistance line and the DNA band of 230 bp was considered as a susceptible line. Similarly, in case of primer RM 390, 70 bp was considered as a resistance line and 112 bp was considered as susceptible line. Basmati, BRRI dhan50, Kalizira Atasail, Bina dhan9, Uknimodhu, BR 34, BR 37 and Zira Katari all of them found as partial resistant to BLB diseases. However, BRRI dhan38 was found as partial or complete susceptible cultivar.

Agrotransformación y evaluación de la resistencia a Phytophthora infestans en Solanum tuberosum L. variedad Désirée

El Oomiceto Phytophthora infestans (Mont.) de Bary, agente causal de la enfermedad denominada tizón tardío, es el principal responsable del déficit en rendimiento y producción en el cultivo de papa a nivel mundial; una de las alternativas a considerar en la lucha contra este patógeno es la integración de secuencias completas de genes R en el genoma de la papa a través de Agrotransformación. El gen Rpi-blb2 (gen R) de la especie silvestre Solanum bulbocastanum Dunal, presenta una amplia resistencia a los aislamientos de P. infestans, haciéndolo un importante candidato en los estudios de mejoramiento genético en plantas. En el presente trabajo se describe la introducción del gen Rpi-blb2 por Agrobacterium tumefaciens en el genoma de la papa variedad Désirée, la caracterización molecular de 29 eventos transformados e infección de plantas completas con el aislamiento POX067 de P. infestans obtenido en el Perú. Los eventos Désirée [Rpi-blb2] 4 y Désirée [ Rpi-blb2] 30, presentaron una resistencia considerable frente a la infección de P. infestans, comprobando de esta manera la transferencia del gen Rpi-blb2 de una especie silvestre a una cultivada mediante transformación genética.

The Oomycete Phytophthora infestans (Mont.) de Bary, the causal agent of the disease known as late blight, is primarily responsible for the decreased in production performance and potato crops worldwide. The integration of the complete R genes sequences in the potato genome using Agro-transformation appears an alternative to be considered in the fight against this pathogen. The Rpi-blb2 gene (R gene) from the wild species Solanum bulbocastanum Dunal shows a broad resistance to isolates of P. infestans, making it an important candidate for plant breeding studies. This paper reports the integration of the Rpi-blb2 gene into potato var. Désirée genome by Agrobacterium tumefaciens - mediated transformation system, the molecular characterization of 29 events transformed and whole plant infection with isolate POX67 of P. infestans from Peru. Désirée events [Rpi-blb2] 4 and Désirée [Rpi-blb2] 30, showed a substantial resistance to P. infestans infection confirming complete transfer of the Rpi-blb2 gene from a wild species to a cultivated species by genetic transformation.