Coffee Disease Research Articles

Lines derived from coffee BA-10 with resistance to Pseudomonas syringae under field conditions with simultaneous natural infections of the pathovars garcae and tabaci

Bacterial-halo-blight and bacterial-leaf-spot are important coffee diseases caused by Pseudomonas syringae pv. garcae and pv. tabaci, respectively. The most suitable method to control these diseases is the use of resistant cultivars. There are no studies on resistance to Pseudomonas syringae (PS) in coffee derived from BA-10 genotypes. Therefore, the aim of this study was to evaluate the resistance to PS in lines derived from BA-10 under field conditions with simultaneous natural infections of the pathovars garcae and tabaci. 38 F4 and two F5 lines derived from BA-10 were evaluated in a field trial in Londrina, PR, Brazil. The Catuaí Vermelho IAC 81 and IAPAR 59 were the susceptible and intermediate resistant controls, respectively. Resistance to PS was evaluated in January 2017 after 45 months of planting. The grading scale varied from 1 to 5, where grade 1 was plants with more resistance and 5 plants more susceptible. Two F5 lines showed 100% of resistant plants (grades 1 and 2) and the F4 line IAPAR 12201 showed 60% of plants with a high level of resistance to PS (grade 1), while the control Catuaí showed no resistant plant. IAPAR 59 and several F4 lines showed high frequency of plants with intermediate resistance to PS

Exogenous application of salicylic acid to control coffee rust

The exogenous application of salicylic acid can induce plant resistance against pathogens. However, little is known about the potential uses of this bioregulator for controlling coffee diseases. In this study, we assessed the effect of applying salicylic acid (SA – 150 mg L-1) on the management of coffee rust (Hemileia vastatrix) in a 7-year-old coffee plantation with low crop load (651.6 kg ha-1 in 2017). For comparison, plants were sprayed with protectant fungicide (copper hydroxide – CH) and standard fungicides (SF) used by local farmers (boscalid, pyraclostrobin + epoxiconazole, and copper hydroxide). Non-treated plants were included as a negative control. Five monthly applications were performed from November 2016 to March 2017. Rust incidence and severity, defoliation, and growth of plagiotropic branches were evaluated monthly. The activity of catalase (CAT), ascorbate peroxidase (APX), superoxide dismutase (SOD) and total proteins was assessed one day after the first, third, and fifth product applications. Compared to untreated plants, SA reduced the severity and incidence of rust from 36.3 to 54.7%, while CH and SF reduced disease from 31.8 to 54.6% and from 83.8 to 88%, respectively. SA reduced defoliation by 54.1%. SA increased the concentration of CAT, APX, and SOD after the first application. However, this effect was not observed after subsequent applications. Foliar application of SA reduces the severity and incidence of coffee rust and defoliation in plants with a low crop load.

Time series analysis of the enhanced vegetation index to detect coffee crop development under different irrigation systems

The coffee crop spectral behavior identification throughout its cycle can contribute to its development monitoring under pest incidence. We aim to identify coffee development through time signatures of enhanced vegetation index (EVI), as well as to evaluate the use of seasonal autoregressive integrated moving average (SARIMA) models to identify coffee trees spectrum-time patterns under different irrigation management and design future scenarios. Three coffee fields were selected under different irrigation systems, whose EVI data of 8 years were obtained from the moderate resolution image spectroradiometer sensor. Each coffee crop model was subjected to residual autocorrelation test and classified according to information criteria, while its accuracy was assessed by means of prediction error measures and agreement index. The estimated and observed EVI values were similar, even for the predicted year. However, in agricultural years during which coffee diseases occurred, the crops showed vegetative vigor below the expected. We concluded that SARIMA models enabled the establishment of a reliable spectral signature expected for coffee crop, which could help with crop management defining, regardless of the irrigation system adopted. Based on the evaluation of divergence between expected and observed spectral signatures, early signs of coffee underdevelopment were detected, which could reduce economic loss risks on its commercial chain.

Characterization and virulence determination of Colletotrichum kahawae isolates from Gidami, Western Ethiopia

Coffee is one of the most essential crops that generate income for Ethiopian economic growth. However, its production faced with many factors primarily biotic entities. Among these, the fungal pathogen /Colletotrichum kahawae/ that induce coffee berry disease (CBD) is the main constraint of coffee production in the country. The pathogen is a very specialized and infects the green berries/fiscal par/which diminishes the income gained from it and disturbs the country’s economy in general and the producers in particular. Regarding to the disease level and related factors, little information is available in Western Ethiopia. Hence, this study was initiated to assess the magnitude of CBD in coffee fields, to characterize and evaluate the virulence of C. kahawae isolates from the study areas of Gidami district. Assessment was done in 9 selected kebeles of 45 total farms starting from July 2017. The results indicated that CBD was prevalence in all assessed areas with the range of 66% to 86% and 16% to 50% disease incidence and severity index (SI), respectively. The highest CBD intensity was observed in higher altitude with a significant positive correlation between disease incidence (r = 0.61) and severity (r = 0.55). Macro and microscopic characterization results revealed isolates diversity in terms of colony color, density, mycelia growth rate and conidial production. Moreover, mycelia growth rate differs significantly (p < 0.001) in the range between 2.2 to 4.3 mm/24 hrs. Similarly, the sporulation capacity widely ranged from 186.1 to 572.3 spores/ml. This were strongly agreed with the virulence test that revealed significant variation (p < 0.001) among isolates and infection percentage also ranged between 34.8% and 88.7%. In all, the study was not only showed the CBD is very important disease of coffee in the study area but also determines the virulence disparity among isolates. To be honest, the diversity/identity of C. kahawae isolates should be confirmed using more other reliable methods thru including additional sample areas as well.

Diagnosis of leaf bacterial diseases of coffee reveals the prevalence of halo blight

ABSTRACT The diagnosis of foliar bacterial diseases in coffee (Coffea arabica), such as halo blight (Pseudomonas syringae pv. garcae), bacterial leaf spot (P. syringae pv. tabaci), bacterial blight (P. cichorii), and dark leaf spot (Robbsia andropogonis), is considered a challenge for plant pathologists. The misidentification has been occurring when the diagnosis is solely based on symptoms and biochemical properties. Thus, the objective of this study was to identify and differentiate species and pathovars of Pseudomonas pathogenic to coffee plants, enabling a survey of the occurrence of these bacteria in the main producing regions of Minas Gerais state, Brazil. Firstly, the pathogenicity of the isolates was confirmed by inoculation in C. arabica cv. Catuaí Vermelho IAC 99. Then, biochemical analyses, combined with, repetitive element-polymerase chain reaction (rep-PCR) and phylogeny based on rpoD gene sequences were used to characterize 84 Pseudomonas isolates from coffee crops and nurseries. Based on rpoD-phylogeny, 73 isolates were identified as P. syringae pv. garcae, five as P. syringae pv. tabaci and six as P. cichorii. The rep-PCR results suggest a high genetic variability in populations of Pseudomonas syringae pv. garcae and P. cichorii. This is the first report of the occurrence of bacterial leaf spot (P. syringae pv. tabaci) in the coffee-producing filed in Minas Gerais State. The findings confirmed the prevalence of P. syringae pv. garcae in coffee production fields in the State and the generated knowledge will contribute for the development of species-specific primers for the identification and detection of this pathogen.

Management of soil borne fungi on coffee

Soil borne fungi can be very importan on coffee plantations and in the nursery. One of the key measure to get vigorous plants in the field is the quality of the seedling and the site of planting. The great majority of the diseases on seedlings came from the nursery. Another source of pathogens is to plant in soil that has suffered clearing of forests. The soil's organic matter contains soil pathogens that attack coffee seedlings after planting. Sometimes plants can die. The main soil borne disease of coffee are: Rhizoctoniosis, Rosellinia root rot, Ceratocystis canker stain and Coffee Wilt Disease. For these reasons the main measures of integrated control is exclusion of the pathogen and avoidance.

Uredospore germination of Hemileia vastatrix and its inhibition by the effect of plant extracts in vitro

Coffee leaf rust, caused by Hemileia vastatrix, is the most important disease of coffee (Coffea arabica L.) in Mexico. It causes production losses of up to 40% and leads to the use of considerable volumes of synthetic fungicides. The main goals of this research were to identify the temperature, pH, incubation time, and luminosity required for in vitro germination of H. vastatrix uredospores and to evaluate the effect of plant extracts on their germination. Uredospores from coffee plants (var. Caturra) grown in the state of Oaxaca, Mexico, were collected and subjected to treatments consisting of combined levels of T°, pH, and incubation time. The treatments were evaluated in darkness and under low-intensity white light (15 W). Uredospore germination occurred in the absence and presence of light. The highest percentage of uredospore germination was 44.95%, which occurred at pH 5.7, between 18 and 24 °C, and with an incubation time of 24 h. The effect of 30 plant extracts was evaluated in terms of inhibition of uredospore germination. The acetone and ethanol extracts of Tribulus terrestris, Datura ferox, Mansoa alliacea, Ricinus communis, and Acacia farnesiana inhibited 100% of uredospore germination. Thus, plant extracts may contribute to the integrated disease management of coffee leaf rust.

Bio-efficacy of new fungicide Pyraclostrobin 133g/l + Epoxiconazole 50g/l SE against coffee leaf rust disease in hill zone of Karnataka

Coffee leaf rust (CLR) is caused by the fungal pathogen, Hemileia vastatrix Berk. & Br. and it is the major disease of coffee in all the coffee growing regions. In the present investigation, evaluation of a new combiproduct fungicide molecule against coffee leaf rust disease was carried out in field conditions during Rabi 2018 and Rabi 2019. The results revealed that, in Rabi 2018 and Rabi 2019, Pyraclostrobin 133g/l + Epoxiconazole 50g/l SE @ 1.50 ml/L showed the least coffee leaf rust disease severity 18.38 PDI and 13.17 PDI respectively which was on par with its higher concentrations (1.75, 3.00 and 4.50 ml/L). Pyraclostrobin 133g/l + Epoxiconazole 50g/l SE @ 1.50 ml/L recorded maximum yield of 690 and 792.66 kg/ha in Rabi 2018 and Rabi 2019 respectively which was on par with other treatments. Pyraclostrobin 133 g/l + Epoxiconazole 50 g/l SE @ 1.5 ml/L can be adopted in spray schedule for integrated disease management of leaf rust (CLR) in coffee.

Evaluation of Tepi and Its Surrounding Coffee Collections Against Major Coffee Diseases at Gera and Tepi

Coffee has for centuries played an important role in the Ethiopian economy and represents the main cash crop cultivated by small-scale farmers for social, economic, political and ecological sustainability. The estimated coffee production area in Ethiopia is 561,761 ha. In Ethiopia, coffee berry disease (CBD), coffee wilt disease (CWD) and coffee leaf rust (CLR) are foremost factors in reducing the quantity and quality of coffee in the country. developing disease resistant landrace coffee varieties and boost the yield with their intrinsic cup quality, a multidisciplinary research program has been designed and implemented at Jimma agricultural research center. To meet this objectives, local land race development program of Tepi 88 coffee collections were started in 2015 and 108 coffee accessions were collected and planted in 2016 at Tepi and Gera research sub centre by Jimma Agricultural Research Center. so, 88 coffee accessions were evaluated for their resistance using visual assessment, attached berry test to CBD, visual to scores CLR and laboratory inoculation test to CWD. There were significant differences among the Tepi coffee collections tested for resistance to coffee berry disease. The range was from 0% (T-83/2011) – 98% (T-63/2011) most of Tepi coffee accessions show susceptable reaction for CBD but most of the accessions show resistance reaction at Gera. Coffee collections were also evaluated for their resistance to coffee leaf rust under field condition at Tepi research center. Highly significant difference among coffee cultivars in percent coffee leaf rust severity was observed (Table 1). Coffee leaf rust disease percent severity varied between 0.17% (T-41/2011) – 21.7% (T-11/2011). There existed highly significant difference among cultivars both in percent wilt seedlings death and incubation period). Disease severity and incubation period on Tepi coffee collections varied between 9.33% (T-06/2011) –97.3% (T-21/2011) and 132 -10 days respectively. Based on over all detailed analysis of field evaluation and greenhouse test investigation for major diseases, and their Yield potentials, Nine Tepi coffee accessions were promoted to Variety verification.

Epitypification of Cercospora coffeicola and its involvement with two different symptoms on coffee leaves in Brazil

Cercospora coffeicola is the causal agent of brown eye spot, an important disease of coffee (Coffea arabica) in Brazil. However, atypical symptom as darker and larger lesions, named black spot, has been reported in field. In this study, we tested the hypothesis that the causal agent of black spot belongs to the same species pathogenic to brown eye spot. Nineteen strains obtained from diseased coffee found in the five largest coffee-producing states of Brazil were characterized by a combination of molecular phylogenic methods, using a multi-locus approach (internal transcribed spacer regions and intervening 5.8S nrRNAs, actin, calmodulin, histone H3, and translation elongation factor 1-alpha), analyses of morphological markers and pathogenicity. Strains from brown eye spot and black spot disease on coffee leaves formed a clade with C. coffeicola strain from Japan. All strains showed same morphological characteristics and caused brown eye spot symptoms in greenhouse. These results confirm that the species associated with brown eye spot and black spot disease on coffee leaves is C. coffeicola. Additionally, an epitype is proposed for C. coffeicola.

Land Suitability for Coffee (Coffea arabica) Growing in Amazonas, Peru: Integrated Use of AHP, GIS and RS

Peru is one of the world’s main coffee exporters, whose production is driven mainly by five regions and, among these, the Amazonas region. However, a combined negative factor, including, among others, climate crisis, the incidence of diseases and pests, and poor land-use planning, have led to a decline in coffee yields, impacting on the family economy. Therefore, this research assesses land suitability for coffee production (Coffea arabica) in Amazonas region, in order to support the development of sustainable agriculture. For this purpose, a hierarchical structure was developed based on six climatological sub-criteria, five edaphological sub-criteria, three physiographical sub-criteria, four socio-economic sub-criteria, and three restrictions (coffee diseases and pests). These were integrated using the Analytical Hierarchy Process (AHP), Geographic Information Systems (GIS) and Remote Sensing (RS). Of the Amazonas region, 11.4% (4803.17 km2), 87.9% (36,952.27 km2) and 0.7% (295.47 km2) are “optimal”, “suboptimal” and “unsuitable” for the coffee growing, respectively. It is recommended to orient coffee growing in 912.48 km2 of territory in Amazonas, which presents “optimal” suitability for coffee and is “unsuitable” for diseases and pests. This research aims to support coffee farmers and local governments in the region of Amazonas to implement new strategies for land management in coffee growing. Furthermore, the methodology used can be applied to assess land suitability for other crops of economic interest in Andean Amazonian areas.

Relationship between Sentinel-2 orbital data and in situ monitoring of coffee rust

Coffee rust (Hemileia vastatrix Berkeley & Broome) is the main coffee disease in Brazil. Coffee rust control is calendar-based and performed by applying chemicals in order to avoid the outburst of disease epidemics. The aim of this work was to identify coffee rust using multispectral orbital sensing through analyses utilising vegetation indices and coffee rust incidence, defoliation and yield data obtained in situ. Field samples were georeferenced using a high-accuracy global navigation satellite system receiver in two plots, in a 42-year-old, leaf rust susceptible coffee cultivar. Conventional chemical control of rust was performed in only one of the plots to serve as control. Coffee rust incidence in areas with and without chemical control was assessed over 5 months, from December 2018 to April 2019, a period with optimal environmental conditions for disease occurrence. Following analyses of different vegetation indices and data sampled in the coffee crop, Pearson’s correlations between the variables were verified. Reported correlations occurred mainly among coffee rust incidence levels in February 2019 and vegetation indices calculated using Sentinel-2 images from August 2018, September 2018 and February 2019 [IRECI r = 0.566; IRECI r = 0.493; NDMI r = − 0.518; NDVI(RE1) r = − 0.562; CI(RE1) r = − 0.573; MSR(RE1) r = − 0.569], in areas without coffee rust control. Indices based on relationships between bands in the Red-Edge and Near Infra-Red regions were more sensitive to spectral changes in vegetation due to variation in coffee rust occurrence over time.

Resistencia genética a la Enfermedad de la Cereza del Café en variedades cultivadas en Colombia.

La enfermedad de las cerezas del café (CBD), antracnosis causada por el hongo Colletotrichum kahawae subsp. kahawae, ha sido registrada solo en África y puede ocasionar pérdidas de producción hasta del 80%. Cenicafé desarrolla variedades resistentes a las enfermedades más limitantes para el cultivo, aún en ausencia de los patógenos en Colombia, usando al Híbrido de Timor (HT) como la principal fuente de resistencia a la roya del cafeto y a CBD. El propósito de este estudio fue conocer la presencia del gen Ck-1 de resistencia a CBD en las principales variedades de café cultivadas en Colombia, establecer la correlación entre la presencia de Ck-1 y la respuesta a inoculación de hipocótilos y explorar las bases genómicas de la resistencia. Los marcadores moleculares ligados a Ck-1 se ubicaron en el cromosoma 1 de Coffea canephora, región genómica con quince genes de resistencia a enfermedades. Se encontraron marcadores para Ck-1 en todas las líneas mejoradas derivadas del HT-1343 y ausentes en las variedades Típica, Borbón y Caturra, y en líneas derivadas del HT-832/1. No hubo correlación entre las formas alélicas de resistencia a CBD y la resistencia medida por inoculación de hipocótilos. La alta frecuencia de formas alélicas asociadas con resistencia a CBD en materiales seleccionados por resistencia a roya sugiere cosegregación de genes de resistencia para ambas enfermedades. La estrategia de variedades multilínea desarrolladas por Cenicafé, que actualmente corresponde a cerca del 80% del café sembrado en el país, hace que la población en general esté protegida ante la eventual llegada del patógeno a Colombia.

Cálculo de grados días de Hypothenemus hampei a través de imágenes satelitales

El café es uno de los cultivos más relevantes en México, su importancia radica en que es un cultivo sustentable, ha sido adoptado y adaptado por comunidades indígenas y genera divisas para el país. Una de las regiones caficultoras más importantes del país, es la del Pacífico Sur, compuesta por Chiapas, Oaxaca y Guerrero donde se produce 53% del café y se encuentra 60% de los productores de este aromático. La presencia de las plagas y enfermedades en el café puede generar pérdidas entre 30 al 50% de la producción. La broca de café Hypothenemus hampei (Ferrari) es el problema entomológico mas grave de este cultivo y su presencia en el país es de hace más de 40 años, actualmente se encuentra en todos los estados que cultivan café. Es por ello, que en este trabajo se generó una metodología práctica que calculó espacialmente los grados días de desarrollo de la broca de café a través de la temperatura de la superficie registrada por imágenes Modis con una resolución espacial de 1 km y con una resolución temporal de un día, monitoreando del 01 de abril de 2018 al 31 de marzo de 2019. Los resultados indicaron que en esta región se puede formar hasta 13 generaciones de la plaga, presentando riesgo en casi todo el año, tanto por el desarrollo como en la dispersión de la plaga. Esta metodología puede apoyar a fortalecer el monitoreo que se hace de la plaga en el país.

Influence of plot features and landscape structure on the epidemics of coffee berry disease (Colletotrichum kahawae Waller & Bridge) in southwest Ethiopia

Coffee berry disease (CBD), caused by Colletotrichum kahawae, is a major fungal disease of coffee in east Africa, and particularly in Ethiopia. To assess the influence of plot features (elevation and slope) and landscape structure (land use types) on the epidemics of CBD, a study was conducted in 2012 and 2013 in 30 smallholders’ coffee plots in southwest Ethiopia. Elevation was the most determining plot feature that influenced the incidence of CBD and berry drops. North-facing coffee plots were affected more by CBD compared to south-facing plots. Landscape structure generally had weak relationship with CBD incidence and berry drops. Overall, coffee growers should give more attention to plot features than landscape structure for CBD management.

Analysis of interactions amongst shade trees, coffee foliar diseases and coffee yield in multistrata agroforestry systems

In complex coffee-based agroforestry systems, quantifying the impact of shade trees on coffee disease regulation and coffee yield is crucial for improving these systems and designing more sustainable ones. To this end, we analyzed interactions amongst shade trees, coffee plants (cv. Catimor), the coffee foliar disease complex and soil characteristics. We studied systems characterized by 40 variables measured in 60 plots located on three farms (monitored for 2 years) in Nicaragua. These variables characterized six system components grouped in six statistical blocks: shade trees (shade percentage and species abundancy), soil characteristics (fertility), foliar diseases, coffee plant characteristics (age and size), coffee growth and yield. We used partial least square path modelling (PLS-PM), i.e. a structural equation modelling approach used to understand and quantify interactions between the six blocks. Shade trees (mostly the associated shade percentage) had direct positive effects on foliar disease severity and incidence and soil quality, while having negative effects on coffee growth and yield. Soil characteristics (carbon, nitrogen, litter index, water infiltration potential) were negatively correlated with foliar diseases. An excessive shade percentage then had an indirect negative effect on coffee growth and yield due to the increased prevalence of foliar diseases. Finding the optimal shade cover can help reduce foliar diseases and enhance coffee berry production. The ‘dose effect’ of shade cover must also be considered because excessive shade, as well as lack of shade, have negative impacts on coffee growth and yield. Overall, effective shade management requires an analysis of trade-offs between soil quality, disease regulation and yield gains. In conclusion, PLS-PM turned out to be a good tool for studying agroecosystem networks and enabled us to put forward some foliar disease management and coffee yield enhancement guidelines.

Machine learning algorithms for forecasting the incidence of Coffea arabica pests and diseases.

Disease and pest alert models are able to generate information for agrochemical applications only when needed, reducing costs and environmental impacts. With machine learning algorithms, it is possible to develop models to be used in disease and pest warning systems as a function of the weather in order to improve the efficiency of chemical control of pests of the coffee tree. Thus, we correlated the infection rates with the weather variables and also calibrated and tested machine learning algorithms to predict the incidence of coffee rust, cercospora, coffee miner, and coffee borer. We used weather and field data obtained from coffee plantations in production in the southern regions of the State of Minas Gerais (SOMG) and from the region of the Cerrado Mineiro; these crops did not receive phytosanitary treatments. The algorithms calibrated and tested for prediction were (a) Multiple linear regression (RLM); (b) K Neighbors Regressor (KNN); (c) Random Forest Regressor (RFT), and (d) Artificial Neural Networks (MLP). As dependent variables, we considered the monthly rates of coffee rust, cercospora, coffee miner, and coffee tree borer, and the weather elements were considered as independent (predictor) variables. Pearson correlation analyses were performed considering three different time periods, 1-10d (from 1 to 10days before the incidence evaluation), 11-20d, and 21-30d, and used to evaluate the unit correlations between the weather variables and infection rates of coffee diseases and pests. The models were calibrated in years of high and low yields, because the biannual variation of harvest yield of coffee beans influences the severity of the diseases. The models were compared by the Willmott's 'd', RMSE (root mean square error), and coefficient of determination (R2) indices. The result of the more accurate algorithm was specialized for the SOMG and Cerrado Mineiro regions using the kriging method. The weather variables that showed significant correlations with coffee rust disease were maximum air temperature, number of days with relative humidity above 80%, and relative humidity. RFT was more accurate in the prediction of coffee rust, cercospora, coffee miner, and coffee borer using weather conditions. In the SOMG, RFT showed a greater accuracy in the predictions for the Cerrado Mineiro in years of high and low yields and for all diseases. In SOMG, the RMSE values ranged from 0.227 to 0.853 for high-yield and 0.147 and 0.827 for low-yield coffee in the coffee borer forecasting.

Unraveling the Complexity of Coffee Leaf Rust Behavior and Development in Different Coffea arabica Agroecosystems.

Crop health management systems can be designed according to practices that help to reduce crop losses by restricting pathogen development and promoting host plant growth. A good understanding of pathogen and host dynamics, which are interdependent, is therefore needed. In this article, we used a holistic approach to explain the behavior of coffee leaf rust (CLR), a major coffee disease. We monitored coffee plant and CLR dynamics simultaneously in plots under different disease management and agroforestry systems. Diseased leaves were also collected to characterize inoculum stock and rust life stages (latent rust area, area with uredospores, necrosis due to rust) through picture analysis. We used structural equation modeling to obtain an overview of CLR pathosystem functioning on a plant scale. This overview integrates processes such as disease dilution by host leaf renewal, direct and indirect effects of fruit load on CLR development, antagonistic effects of shading depending on rust life stages, the tonic effect of copper-based fungicides on leaf retention, and effects on rust life stages depending on fungicide types. From our results, we also deduced that the inoculum stock could be calculated in unsprayed plots from the rust area with uredospores, with uredospores at 58 × 103 cm-2, on average.

Multispectral radiometric characterization of coffee rust epidemic in different irrigation management systems

Coffee rust (Hemileia vastatrix Berk. & Br.) is one of the most prominent diseases in coffee (Coffea arabica L.) and causes serious damage to the crop. The pathogen incubation period may be long for about 30 days and 10% incidence of rust may result in 3 times more disease few days after the signals of rust appear in the leaves, even in the absence of new infections. The objective of this study was to evaluate the applicability of coffee crop monitoring under different irrigation systems by orbital radiometry, exploring the spectral signature and spectral, spatial and temporal pattern of rust incidence in the coffee field. The study was carried out in four areas of coffee plantations in Carmo do Rio Claro, Minas Geris, Brazil, between August 2012 and December 2014, under self-propelled, drip, center pivot irrigation systems and rainfed system. Fifteen Landsat-7/ETM + and Landsat-8/OLI-TIRS images were used, trying to establish a better sequence of images between in situ data of rust incidence in the coffee leaves and coffee leaf growth evaluated by sample meshes in the field along the time. Space-time disease incidence distribution maps, Pearson correlation and reflectance spectral signatures were used to evaluate coffee rust progress in the different irrigation fields. The highest coffee rust incidence occurred in August and corresponded to the values of lower NIR reflectance for all evaluated areas, independently of the irrigation management system. In the visible, SWIR-1 and SWIR-2 spectral regions, there were higher reflectance values in the rainfed area when compared to irrigated areas in rainy periods. There was a greater spectral and temporal variation of rust in the center pivot irrigation system when compared to the other irrigation management systems, presenting high values ​​of average incidence of rust above 30% in the periods close to the harvest period, from June to August 2013 and 2014. The high incidence of rust associated with coffee fruit harvest probably led to a reduction in plant leaf growth in center pivot and rainfed fields. There was a negative correlation between near infrared and rust in the self-propelled and center pivot management systems. High coffee rust incidence values mainly in center pivot and rainfed coffee fields determined reduction in the average reflectance of NIR and green and increase reflectance in red, SWIR-1 and SWIR-2 when compared to periods with lower rust in the coffee fields.

Kanker Batang: Penyakit Baru pada Kopi di Lampung

Stem Canker: A New Disease of coffee in LampungStem cancer is a new disease that has attacked smallholder coffee plantations in Lampung since 2010. The cause of the disease was unknown. This study aims to describe the symptoms of the disease, the incidence of the disease in the affected plantation, and identify morphologically and molecularly the canker pathogens of the coffee stem canker diseases. All stages of Koch’s postulate were carried out in laboratories and greenhouses. The isolated pathogens were morphologically characterized by colony shape and color as well as the conidia shape and size. Molecular identification was carried out by using a general primer (ITS1 and ITS4) and followed by sequencing. The main symptoms of the disease are stem cancer and dieback, as well as more infecting older plants. Pathogen of the coffee stem canker disease that attacks coffee plants in Lampung has been identified as Fusarium solani which has 99% homology with F. solani KY245947.1.