Coffee Leaf Rust Severity Research Articles

Biocontrol of Hemileia vastatrix, the Causal Agent of Coffee Leaf Rust, by Paenibacillus sp. NMA1017.

Coffee leaf rust (CLR), caused by Hemileia vastatrix, is considered a highly important phytosanitary problem in Mexico. Currently, there are few microorganisms used as biocontrol alternatives to chemical control of CLR in organic coffee fields in Mexico. This study evaluates the use of Paenibacillus sp. NMA1017 as a biocontrol agent to inhibit the development of H. vastatrix in in vitro and in vivo (greenhouse) experiments. Hemileia vastatrix urediniospores were placed on water agar plates, and then Paenibacillus sp. NMA1017 was inoculated simultaneously or 8 h later. Urediniospores germination rate was reduced by 94% when the NMA1017 strain was inoculated simultaneously with the urediniospores and reduced by 38% when NMA1017 was inoculated 8 h later. Experiments with 8-month-old Bourbon coffee plants that were infected with H. vastatrix showed that disease incidence was reduced by 38, 90, and 50% when NMA1017 was applied 8 days before, simultaneously, or 8 days after the application of H. vastatrix, respectively. Paenibacillus sp. NMA1017 also reduced the severity of CLR on the leaves by up to 62%. The germination urediniospores of other rust pathogens such as Puccinia sorghi (maize leaf rust), Puccinia triticina (wheat leaf rust), Puccinia graminis f. sp. tritici (black stem rust of wheat), Uromyces striatus (alfalfa leaf rust), and Phragmidium sp. (rosebush leaf rust) were also inhibited. Use of the potential biocontrol agent Paenibacillus sp. NMA1017 might help reduce the application of chemical fungicides for the control of CLR, making coffee a more sustainable crop and providing management options for organic coffee growers.

Diversity of Leaf Fungal Endophytes from Two Coffea arabica Varieties and Antagonism towards Coffee Leaf Rust.

Coffee has immense value as a worldwide-appreciated commodity. However, its production faces the effects of climate change and the spread of severe diseases such as coffee leaf rust (CLR). The exploration of fungal endophytes associated with Coffea sp. has already found the existence of nearly 600 fungal species, but their role in the plants remains practically unknown. We have researched the diversity of leaf fungal endophytes in two Coffea arabica varieties: one susceptible and one resistant to CLR. Then, we conducted cross-infection essays with four common endophyte species (three Colletotrichum sp. and Xylaria sp. 1) and Hemileia vastatrix (CLR) in leaf discs, to investigate the interaction of the endophytes on CLR colonisation success and severity of infection. Two Colletotrichum sp., when inoculated 72 h before H. vastatrix, prevented the colonisation of the leaf disc by the latter. Moreover, the presence of endophytes prior to the arrival of H. vastatrix ameliorated the severity of CLR. Our work highlights both the importance of characterising the hidden biodiversity of endophytes and investigating their potential roles in the plant-endophyte interaction.

Response of arabica coffee populations on coffee leaf rust in two weather conditions in North Sumatra, Indonesia

Coffee leaf rust (CLR) disease is seriously threatening the sustainability of coffee production in many countries. The incidence and severity as CLR parameters generally depend on the coffee plant, pathogen, and environment. Therefore, this study aimed to determine the effect of arabica coffee populations and weather conditions on CLR parameters. The study was carried out using a field experiment with seven groups of arabica coffee populations in different weathers in North Sumatra Province, Indonesia. The results showed that the arabica coffee population P7 from District Toba had high resistance to wet weather. Furthermore, all the population groups showed higher degree of CLR parameters in dry than wet weather, while a significant interaction between the population and the weather was observed on branch rust incidence, leaf rust incidence, and severity. Moreover, H. vastatrix races were probably varied and had different adaptability to weather changes, which was the most decisive factor for the dispersal and severity of CLR. The CLR parameters in the dry weather did not correlate with the parameters in the wet weather and vice versa. The total rainfall and the number of the rainy day reduced the CLR dispersal and severity.

Impact of climate on a host–hyperparasite interaction on Arabica coffee in its native range

Abstract Natural enemies of plant pathogens might play an important role in controlling plant disease levels in natural and agricultural systems. Yet, plant pathogen–natural enemy interactions might be sensitive to climatic changes. Understanding the relationship between climate, plant pathogens and their natural enemies is thus important for developing climate‐resilient, sustainable agriculture. To this aim, we recorded shade cover, daily minimum and maximum temperature, relative humidity, coffee leaf rust and its hyperparasite at 58 sites in southwestern Ethiopia during the dry and wet season for 2 years. Coffee leaf rust severity was positively related to the maximum temperature. Hyperparasite severity was higher when the minimum temperature was low (i.e. in places with cold night temperatures). While canopy cover did not have a direct effect on rust severity, it reduced rust severity indirectly by lowering the maximum temperature. Canopy cover had a direct positive effect on the hyperparasite severity during one surveying period. Synthesis and applications. Our findings highlight that coffee leaf rust and its hyperparasite are both affected by shade cover and temperature, but in different ways. On the one hand, these niche differences lead to the worrying prediction that levels of coffee leaf rust will increase, and its hyperparasite will decrease, with climate change. On the other hand, these niche differences between coffee leaf rust and its hyperparasite provide opportunities to develop strategies to manage the environment (such as shade cover and microclimate) in such a way that the rust is disfavoured and the hyperparasite is favoured.

Agro‐morphological characterization and diversity analysis of Coffea arabica germplasm collection from INIA, Peru

AbstractCoffee (Coffea arabica L.) plays a major role in the economy of Peru and the world. The present study aims to elucidate the agro‐morphological variability of coffee genotypes maintained in the National Institute of Agrarian Innovation (INIA) germplasm collection. Therefore, 20 vegetative, reproductive, and phytosanitary traits of 162 coffee accessions of INIA's germplasm collection were evaluated and analyzed. Correlation results indicate that a simultaneous selection of characters, such as number of branches per plant, number of nodes per branch, leaf area, and weight of a hundred fruits, can contribute to increase coffee yields. Additionally, coffee yield was negatively correlated with the incidence and severity of coffee leaf rust, and interestingly the occurrence of small and compact coffee plants with high resistance to the disease was also found. The analysis of Tocher and Mahalanobis D2 determined the formation of 10 groups of divergent coffee accessions; where clusters 1 (accession codes 20, 29, 38, 54, 67, 71, 117, 24, 26, and 27), 5 (accession codes 46 and 53), 9 (accession code 159), and 10 (accession code 203) group promising accessions that can be used in breeding programs. Principal component analysis showed that at least five of its principal components managed to explain 70.01% of the total variation in the collection. Finally, the high coefficients obtained for the phenotypic, genotypic, and heritability variation confirm the existence of additive genes in the evaluated population, that would ensure the success of coffee breeding programs based on the selection of traits of agronomic importance.

Leaf functional traits and pathogens: Linking coffee leaf rust with intraspecific trait variation in diversified agroecosystems.

Research has demonstrated that intraspecific functional trait variation underpins plant responses to environmental variability. However, few studies have evaluated how trait variation shifts in response to plant pathogens, even though pathogens are a major driver of plant demography and diversity, and despite evidence of plants expressing distinct strategies in response to pathogen pressures. Understanding trait-pathogen relationships can provide a more realistic understanding of global patterns of functional trait variation. We examined leaf intraspecific trait variability (ITV) in response to foliar disease severity, using Coffea arabica cv. Caturra as a model species. We quantified coffee leaf rust (CLR) severity-a fungal disease prominent in coffee systems-and measured key coffee leaf functional traits under contrasting, but widespread, management conditions in an agroforestry system. We found that coffee plants express significant ITV, which is largely related to shade tree treatment and leaf position within coffee canopy strata. Yet within a single plant canopy stratum, CLR severity increased with increasing resource conserving trait values. However, coffee leaves with visible signs of disease expressed overall greater resource acquiring trait values, as compared to plants without visible signs of disease. We provide among the first evidence that leaf traits are correlated with foliar disease severity in coffee, and that functional trait relationships and syndromes shift in response to increased disease prevalence in this plant-pathogen system. In doing so, we address a vital gap in our understanding of global patterns of functional trait variation and highlight the need to further explore the potential role of pathogens within established global trait relationships and spectra.

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

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

Temporal progress of coffee leaf rust and environmental conditions affecting severity in Veracruz State, Mexico

Coffee is an important crop in Mexico. Unfortunately, coffee production has been affected by coffee leaf rust (CLR). The severity of this infection occurs with variations along the year described before in different coffee-producing regions worldwide. For Veracruz, there are available reports of weekly CLR severity, but this information is only descriptive. We analyzed variations along the year of CLR severity in Veracruz with data from municipal weekly reports provided by Mexico’s federal government phytosanitary epidemiological monitoring coffee program. We selected reports dated in 2018 from nine municipalities and after calculations of mean monthly severity values, we conducted a one-way ANOVA (months as factors) of severity data. We compared this information with other coffee-producing regions. Additionally, we explored the association of temperature, rainfall, and altitude with CLR severity using Principal Component Analysis and multiple linear regressions. Temperature and rainfall data were obtained from Mexican National Meteorological Service. We found that CLR severity in January, October, November, and December (months of harvest period) was significantly higher than values from March-June. During the harvest period, coffee plants allocate resources mainly for fruiting which competes in resources for other tasks such as defense and leaf growth, so this competition of resources can explain the positive relationship found between fruit load and CLR severity. This monthly variation of severity was similar to those reported in Chiapas, Guatemala, Colombia, Uganda, and Ethiopia. Our model (R2 = 0.401) showed a significant and negative effect of altitude and medium temperature on CLR severity, while the effect of rainfall was positive. With our study, we suggest applications of fungicides in March-June when coffee plantations are in leaf phenophase. Key words: Altitude; Coffea arabica; Hemileia vastatrix; phenophase.

Shade management and pruning in two coffee varieties vs. plant growth and leaf rust in the Peruvian Amazon

Coffee leaf rust (CLR) is a fungal infection which is devastating susceptible coffee plantations throughout the South American region in the last years. The objective of this study was to analyze the effects of shade trees management and pruning in two coffee varieties against coffee leaf rust in the Peruvian Amazon. The experimental design was a randomized complete block with factorial scheme 2A×2B×4C with 16 treatments and four repetitions, making a total of 64 experimental units, in which each experimental unit had 16 coffee plants. The studied factors were agroforestry system (A), coffee varieties (B), and pruning methods (C). The data were statistically examined by analysis of variance and mean comparisons using Tukey test. It was found that plant growth was favored by the use Inga shade and recepa pruning in Typica variety. Also, the use of polyculture-shaded coffee with about 40 % of shadow, and recepa, a pruning method which consists of cutting the stem of the coffee plants at 40 cm from the ground, reduce the incidence and severity of CLR in coffee plants. The incidence and severity of CLR was lower in the Typica variety as comparted to Pache variety. This study confirms that a shadow management and pruning coffee plants stimulate the growth of new branches and reduce incidence and severity of CLR in coffee plantations.

Management of coffee leaf rust using L-glutamic acid biofertilizer combined with fungicide

The use of biofertilizers is a potential tool for the management of crop diseases. Coffee leaf rust, which is commonly controlled by triazole and strobilurin fungicides, is one of the main phytosanitary challenges associated with coffee cultivation. However, the indiscriminate use of such fungicides may be harmful to the environment and human health, in addition to having a negative impact on coffee exports. The aim of this study was to evaluate the effect of foliar application of L-glutamic acid on the incidence and severity of coffee leaf rust in the southern region of Minas Gerais, Brazil. A biofertilizer made of sugarcane molasses fermented by the bacterium Corynebacterium glutamicumwas used in combination with 25% L-glutamic acid and a fungicide of the triazole group registered for crops. The experimental design adopted was randomized blocks with four replications (eight plants per replicate) and seven treatments: fungicides, control test, 0.8 L ha-1 of biofertilizer, combinations of 0.04, 0.06, 0.08, and 0.1 L ha-1 of biofertilizer and fungicide.Three treatments were initially applied in a preventive way, before the rainy season, and then at intervals of 60 days. After seven months of treatment, we observed that coffee leaf rust incidence was significantly lower in coffee plants treated with combined products when compared to treatments of either fungicide or biofertilizer only, with a reduction of 56% and 45%, respectively, being observed. Among the combinations of biofertilizer and fungicide, coffee leaf rust incidence reduced with an increase in the biofertilizer dose, such thatthe disease incidence in plants treated with a dose of 0.1 L ha-1was 58% lower than that in plants treated with fungicide only. No differences in disease severity were observed among the treatments. In conclusion, the use of a combination of biofertilizer and fungicide is more effective for the management of coffee leaf rust than the use of the isolated products. Key words: Amino acid; Hemileia vastatrix; Incidence; Severity.

Detecting coffee leaf rust with UAV-based vegetation indices and decision tree machine learning models

Coffee leaf rust (CLR) is one of the most devastating leaf diseases in coffee plantations. By knowing the symptoms, severity, and spatial distribution of CLR, farmers can improve disease management procedures and reduce losses associated with it. Recently, Unmanned Aerial Vehicles (UAVs)-based images, in conjunction with machine learning (ML) techniques, helped solve multiple agriculture-related problems. In this sense, vegetation indices processed with ML algorithms are a promising strategy. It is still a challenge to map severity levels of CLR using remote sensing data and an ML approach. Here we propose a framework to detect CLR severity with only vegetation indices extracted from UAV imagery. For that, we based our approach on decision tree models, as they demonstrated important results in related works. We evaluated a coffee field with different infestation classes of CLR: class 1 (from 2% to 5% rust); class 2 (from 5% to 10% rust); class 3 (from 10% to 20% rust), and; class 4 (from 20% to 40% rust). We acquired data with a Sequoia camera, producing images with a spatial resolution of 10.6 cm, in four spectral bands: green (530–570 nm), red (640–680 nm), red-edge (730–740 nm), and near-infrared (770–810 nm). A total of 63 vegetation indices was extracted from the images, and the following learners were evaluated in a cross-validation method with 10 folders: Logistic Model Tree (LMT); J48; ExtraTree; REPTree; Functional Trees (FT); Random Tree (RT), and; Random Forest (RF). The results indicated that the LMT method contributed the most to the accurate prediction of early and several infestation classes. For these classes, LMT returned F-measure values of 0.915 and 0.875, thus being a good indicator of early CLR (2 to 5% of rust) and later stages of CLR (20 to 40% of rust). We demonstrated a valid approach to model rust in coffee plants using only vegetation indices and ML algorithms, specifically for the disease's early and later stages. We concluded that the proposed framework allows inferring the predicted classes in remaining plants within the sampled area, thus helping the identification of potential CLR in non-sampled plants. We corroborate that the decision tree-based model may assist in precision agriculture practices, including mapping rust in coffee plantations, providing both an efficient non-invasive and spatially continuous monitoring of the disease.

Factors influencing the performance of phosphites on the control of coffee leaf rust

ABSTRACT This study investigated the effect of different phosphites on the control of coffee leaf rust (CLR) caused by Hemileia vastatrix, considered the major disease affecting coffee yield worldwide. Three-month-old coffee plants were sprayed with two doses each of the phosphite solutions (standar., and double), as follows: K (40% P2O5; 1.., and 3 mL∙L-1), K (30% P2O5; ., and 6 mL∙L-1), Cu (2.., and 5 mL∙L-1), Mn+Zn (., and 6 mL∙L-1., and Na (., and 6 mL∙L-1) 24 h before being inoculated with H. vastatrix. Leaves were not washed or washed with deionized water after the foliar phosphites spray. Plants sprayed with water served as the control treatment. Inoculation was performed on the abaxial side of the first pair of expanded leaves using a camel hairbrush with a suspension of urediniospores (1 mg per leaf). All phosphites applied at the standard doses (from 1.5 to 3 mL∙L-1) reduced the total number of pustules (TNP) per leaf by 28-69% regardless of washing treatment. The biggest reductions were observed for Cu phosphite, which decreased the TNP per leaf by 6., and 69% withou., and with leaf washing, respectively. A similar trend was observed when the double doses of phosphites (from 3 to 6 mL∙L-1) were used, though Na phosphite without leaf washin., and Mn/Zn phosphite withou., and with leaf washing were not efficient to reduce the TNP per leaf. Without leaf washing, only C., and Na phosphites decreased CLR severity at the standard doses (53-61%), whereas all phosphites, except the Mn/Zn phosphite, reduced CLR severity at the double dose. The CLR severity was decreased using K 30%, K 40., and Cu phosphites when applied at the standard doses with leaf washing (41-59%). With double doses, only C., and Na phosphites decreased CLR severity by 55% for both treatments. In conclusion, the efficiency of the phosphites for CLR control varied according to the accompanying cation, dos., and washing conditions. The Cu phosphite resulted in the best CLR control regardless of the dose use., and the washing conditions.

Dynamics of severity of coffee leaf rust (Hemileia vastatrix) on Coffee, in Chanchamayo (Junin-Peru)

Introduction. Coffee (Coffea arabica L.) is an important crop in producing countries like Peru, where approximately two million families depend on its production, distribution, and marketing. But in recent years, climate change has increased the presence of coffee leaf rust - CLR (H. vastatrix), a disease that has decreased Peruvian production by up to 27%. Objective. Monitor the severity of CLR in different genotypes of coffee cv. Typica from April-2017 to March-2018. Material and methods. The experiment was carried out in the coffee germplasm bank at the Development Regional Institute (IRD)-Selva of the Universidad Nacional Agraria La Molina. The severity and the area under the disease progress curve (AUDPC) in the lower, middle, and upper part of coffee trees were quantified. Result. There was high severity and AUDPC in the dry season (low precipitation) compared to the rainy season (high precipitation). Severity and AUDPC gradually decreased from the bottom to the top of the plant (lower&gt;middle&gt;upper). Also, UNACAF-24A, UNACAF-16, UNACAF-158, and UNACAF-162 genotypes stood out by showing lowest severity (0-1.1 %) and AUDPC (0-714) in the experiment. Conclusion. In this experiment, the genotypes in dry season presented high peaks of severity and UDPC of CLR, meanwhile, in rainy season the presence of CLR was lower. However, in both seasons, severity and AUDPC gradually decreased from the lower third to the upper thirf of the plant. Finally, UNACAF-24A, UNACAF-16, UNACAF-158, and UNACAF-162 presented the lowest degrees of severity of CLR.

Standard area diagram with color photographs to estimate the severity of coffee leaf rust in Coffea canephora

Color photographs represent the symptoms of the disease as observed in the field, favoring the visual estimation of severity. In order to increase the accuracy, repeatability and reproducibility of Coffea canephora L. rust severity estimates, this study was carried out to elaborate and validate a standard area diagram (SAD) constructed with color photographs (SADcp). To do so, we collected leaves with different intensities of symptoms in crops, and the actual severity was determined with the aid of the software QUANT. The intermediate levels of the scale were determined based on the frequency distribution of severity values. The validation of the diagram was performed by 13 raters who estimated disease severity in 50 leaves of C. canephora with different intensity of symptoms. One assessment without the standard area diagram and two assessments with the diagram were performed at intervals of seven days. Data were analyzed by linear regression and Lin's concordance correlation coefficient. The accuracy, precision, repeatability and reproducibility of the estimates were evaluated. To compare the efficiency of SADcp with the existing scale constructed with two-color diagram (SAD2col), these procedures were performed with both scales. Without the scale and with the SAD2col diagram, the raters overestimated the severity of the disease. With the use of SADcp, the raters presented better levels of accuracy, precision, reproducibility and repeatability in the estimates, compared to when they did not use SAD, or when they used SAD2col. Therefore, SADcp was suitable for estimating the severity of coffee leaf rust in C. canephora.

Agronomic performance of coffee in response to framework pruning in cycles of the “safra zero”

In this paper, we aimed at selecting genotypes of Coffea arabica L. that are responsive to framework prunin, with high productive potential and desirable agricultural features. We evaluated 18 progenies in the F5 generation, 8 of them being from the group Catucai (breeding of seedlings of Red Catuai with coffee seeds of the Icatu germplasm) and ten descendants from the Timor Hybrid (breeding of the Red and Yellow Catuai with the Timor Hybrid), as well as two commercial cultivars as witnesses (Tupi IAC 1669-33 and Obata IAC 1669-20). The experiment was carried out at the experimental field of the Federal University of Lavras. The coffee was pruned in August 2014 after the sixth crop and once again in August 2016, being two cycles in the “safra zero” system. The design used was in randomized blocks (RBD) with three repetitions and 20 treatments (18 progenies and two commercial cultivars) totaling 60 experimental plots. We evaluated the area under the progress curve of incidence and severity of leaf rust and cercosporiosis, the productivity (sacs ha-1), sieve #16 and over (%), mocha-type grains (%) and apparent specific mass of grains (ton.m3). The genotype 12 (H516-2-1-1-18-1-4) was responsive to the framework pruning and kept its productivity stable in both pruning cycles, being efficient in such system of crop conduction, besides presenting low incidence and severity of coffee leaf rust and cercosporiosis and high sieve. Key words: Timor hybrid; Cercosporiosis; Leaf rust.

Landscape context and plot features influence the epidemics of coffee leaf rust (Hemileia vastatrix) in southwest Ethiopia

From 2013 to 2015, a study was conducted on 29 coffee plots to assess the influence of landscape context and plot features on the epidemics of coffee leaf rust (CLR) descriptors in Gumay and Setema districts, Southwest Ethiopia. Maximum CLR severity and number of sporulating lesion density per leaf was significantly correlated with different land use types (tree density at 100 m, 200 m, pasture and crop lands at 200 m circular radius), and plot features (altitude, North-South aspect, East-West aspect and leaf area index) over different years of observation. High tree density in the surrounding coffee plots significantly increased the severity of the disease. There was a general decreasing trend of CLR severity, sporulating lesion density and proportion of leaf fall over the altitudinal gradient. The interaction of landscape context with CLR descriptors found were so complex and need further detail analysis.

Geographical distribution of the incubation period of coffee leaf rust in climate change scenarios

Abstract: The objective of this work was to simulate the geographical distribution of the incubation period of coffee leaf rust in Coffea arabica, using data of two regional climate models, Eta-HadGEM2-ES and Eta-MIROC5. The scenario of high greenhouse gas emission (RCP 8.5 W m-2) was used for the states of Minas Gerais and São Paulo, Brazil, for current and future climate scenarios. The behavior of six different regression equations for incubation period (IP), available in the literature, was also analyzed as affected by data from the regional climate models. The results indicate the possibility of an increase in the affected area in the studied region, when the IP is less than 19 days, from 0.5% for Eta-MIROC5 to 14.2% for Eta-HadGEM2-ES. The severity of coffee leaf rust in future scenarios should increase in the hottest and wettest months of the year, extending to the driest and coldest months. The potential of rust infection is estimated differently by the studied equations. In higher temperature scenarios, the Kushalappa &amp; Martins equation indicates a very high severity potential.

Machine learning prediction of coffee rust severity on leaves using spectroradiometer data

The interest in using remote sensing data in agriculture, including plant disease assessments, has increased considerably in the last years. The satellite-based Sentinel-2 MultiSpectral Imager (MSI) sensor has been launched recently for multispectral vegetation condition assessment for agricultural and ecosystem applications. The aim of this pilot study conducted in the greenhouse using a hand-held spectroradiometer was to assess the utility of the same wavebands as used in the Sentinel-2 MSI in assessing and modeling coffee leaf rust (CLR) based on the non-linear radial basis function-partial least squares regression (RBF-PLS) machine learning algorithm, compared with ordinary partial least squared regression (PLSR). The RBF-PLS derived models satisfactorily described CLR severity (R 2=0.92 and RMSE=6.1% with all bands and R 2=0.78 and RMSE=10.2% with selected bands) when compared with PLSR (R 2 = 0.27 and RMSE = 18.7% with all bands and R 2 = 0.17 and RMSE = 19.8% with selected bands). Specifically, four bands, B2 (490 nm), B4 (665 nm), B5 (705 nm) and B7 (783 nm) were identified as the most important spectral bands in assessing and modeling CLR severity. Better accuracy was obtained for most severe levels of CLR (R 2=0.71 using all variables) than for moderate levels (R 2=0.38 using all variables). Overall, the findings of this study showed that the use of RBF-PLS and the four Sentinel-2 MSI bands could enhance CLR severity estimation at the leaf level. Further work will be needed to extrapolate these findings to the crop level using the Sentinel-2 platform.

DMI and QoI fungicides for the control of coffee leaf rust

This study investigated the ability of different triazole and strobilurin fungicides either alone or combination when applied to the leaves and triazole to the soil for control of Coffee Leaf Rust (CLR). The experiments were performed in a greenhouse using three month-old coffee seedlings, and in the field with five years old plants using the susceptible variety ‘Catuai vermelho’, at elevation of 750 m, from 2010 to 2012, in Vicosa, Minas Gerais State, Brazil. The effects of triazole (triadimenol, cyproconazole and epoxiconazole) and strobilurin (azoxystrobin, trifloxystrobin, pyraclostrobin) was first studied in a greenhouse to evaluate the translaminar effect on CLR control. Based on the results obtained in the greenhouse, a field experiment was performed to evaluate the effect of triazole applied to the soil and triazole + strobilurin sprayed on CLR control and the effect on coffee berry yield of the plants. The different fungicides applied in the greenhouse reduced CLR severity by 8.9 % (trifloxystrobin), 79.4 % (azoxystrobin), 82.0 % (triadimenol), 93.2 % (cyproconazole), 96.6 % (epoxiconazole) and 98.5 % (pyraclostrobin) compared to that in the control plants. In the field experiment triazole + strobilurin fungicides provided effective CLR control. The co-application of epoxiconazole and pyraclostrobin or azoxystrobin sprayed twice resulted in the most effective CLR control and maintained the highest coffee berry yield. The incidence of CLR was 83.5, 54.0 and 78.5 % for the control treatments, whereas the incidence did not exceeded 24.4, 37.0 and 39.0 % on the sprayed plants. The average coffee berry yield increased by 33.9 % (lowest value) when applying triadimenol to the soil in November followed by cyproconazole + trifloxystrobin sprayed in December and February, and increased by 99.1 % (highest value) in the treatment with epoxiconazol + pyraclostrobin sprayed in December and March compared with plants that did not receive any fungicide application. The control treatment and that of triadimenol applied to the soil in November followed by cyproconazole + trifloxystrobin sprayed in December and February yielded less than 1800 (1320 to 1800) kg/ha of processed coffee, whereas the other treatments more than 2100 (2142 to 2676) kg/ha. Treatments with cyproconazole applied to the soil in November followed by cyproconazole + azoxystrobin sprayed on the leaves in December and February, epoxiconazol + pyraclostrobin sprayed on the leaves in December and March, and cyproconazole + azoxystrobin sprayed on leaves in December, February and April yielded more than 2340 (2340 to 2676) kg/ha of processed coffee. This is the first report indicating that a triazole fungicide applied to the soil and triazole + strobilurin fungicide sprayed on the leaves, efficiently controlled CLR and significantly increased coffee berry yield for three seasons.

Photosynthetic and antioxidative alterations in coffee leaves caused by epoxiconazole and pyraclostrobin sprays and Hemileia vastatrix infection

Coffee leaf rust (CLR), caused by Hemileia vastatrix, is a major disease affecting coffee production worldwide. In this study, an in-depth analysis of the photosynthetic performance of coffee leaves challenged or not with H. vastatrix and sprayed with either epoxiconazole (EPO) or pyraclostrobin (PYR) was performed by combining chlorophyll a fluorescence images, photosynthetic pigment pools and the activities of chitinase (CHI), β-1,3-glucanase (GLU), peroxidase (POX) and catalase (CAT). The CLR severity was higher in the control plants, but reduced in plants sprayed with both PYR and EPO. Also, the CLR severity was reduced in plants sprayed with PYR compared with plants sprayed with EPO. Plants sprayed with either EPO or PYR showed maximal photosystem II quantum efficiency (Fv/Fm) values ranging from 0.78 to 0.80, which were quite similar to those obtained with inoculated plants (values ranging from 0.74 to 0.77). The decreases in the Fv/Fm ratio values and parallel increases in the F0 values in the inoculated plants, which were not observed in the control plants (sprayed with water) and were confirmed by images of the initial fluorescence (F0) and Fv/Fm parameters in the regions of the leaf tissue containing pustules and in the asymptomatic leaf tissue, indicated that photosynthesis was negatively impacted. When effective photosystem II quantum yield (Y(II)) values approached zero with a high photosynthetic photon flux density, high values of quantum yield of regulated energy dissipation (Y(NPQ)) in association with a high carotenoid concentration were noted in the inoculated plants sprayed either with PYR or EPO. The increased CLR severity in inoculated plants in contrast to inoculated plants sprayed with either PYR or EPO was associated with greater POX activity and a reduced photosynthetic pigment concentration. POX and CAT activities were increased in inoculated plants sprayed with either EPO or PYR when compared with control plants. CHI and GLU activities were maintained at high levels in the leaves of inoculated plants, regardless of the fungicide sprayed, indicating that CHI and GLU are less important for coffee resistance against CLR. The results of the present study clearly demonstrated that plants sprayed with either EPO or PYR showed milder CLR symptoms with adequate photosynthetic performance and optimal conditioning of their antioxidant systems.