Leaf Rust Severity Research Articles

Variability of Genotypes of Arabica Coffee (Coffea arabica L.) in Coffee Leaf Rust (Hemileia vastatrix)

Coffee leaf rust (Hemileia vastatrix) caused large damage on Arabica coffee in Asia, Africa, and America. The resistant genotypes released to farmers in Brazil were developed from the existing cultivars. However, the cultivars of Arabica coffee existing in North Sumatra Province of Indonesia is not yet researched to find resistant genotypes. The goal of this reseach was to determine variability of coffee leaf rust and leaf morphology. In total of 84 genotypes growing in this Province were selected using nested design. Data was analyzed using nested design, correlation, stepwise regression, and hierarchical cluster analysis. This research revealed leaf rust severity had high genotypic variation, low heritability, and high genetic adveance. Ratios of leaf morhology showed moderate to high genotypic variation and heritabilities. Leaf rust severity (y) significantly correlated with both ratio of leaf length with leaf area (x1) and ratio of leaf length with leaf width (x2) with equation y = 2,04 + 62,48x1 3,95x2 with coefficient of multiple correlation R = 0,470**. By using leaf rust severity and these two ratios in cluster analysis, one cluster comprised 18 genotypes with medium leaf rust severity. It could be concluded that resistant genotypes of Arabica coffee might be possible to develop from the existing cultivars. Leaf rust severity might not be used as selection parameter in breeding for leaf rust resistance.

Effect of leaf rust disease on photosynthetic rate, chlorophyll contents and grain yield of wheat

The objective of the present study was to investigate what extent the leaf rust disease severity affects the photosynthesis and grain yield in wheat. This was done by estimating disease severity, photosynthetic rate, chlorophyll contents and grain yield loss in six wheat varieties under the natural and fungicide treated conditions. Among six wheat varieties/lines (Galaxy-13, Millat-11, Lasani-08, Faisalabad-08 and two wheat lines NW-1-8183-8 and NW-3-3341-7), the mean severity level of leaf rust was the highest on Galaxy-13 and Faisalabad-08, however, grain yields were also higher in Galaxy-13, Millat-11 and FSD-08. Wheat lines NW-1-8183-8, NW-3-3341-7 and wheat variety Millat-11 showed less severity with high yield. One application of fungicide, propiconazole reduced the rust infections significantly and enhance the photosynthetic rate and chlorophyll contents, resulting in significantly higher yield in fungicide treated plots. On the basis of leaf rust severity and grain yield assessment, wheat varieties Galaxy-13 and FSD-08 were found highly tolerant against rust diseases. Maximum cost-benefit ratio was found in NW-3-3341-7 (1:12.2) when treated against rust fungicide. The study concluded that rust disease significantly reduced the grain yield when not protected by fungicide. Integration of host resistance with minimum fungicide application can reduce the deleterious effect of leaf rust and gives maximum net returns.

Mapping quantitative trait loci associated with leaf rust resistance in five spring wheat populations using single nucleotide polymorphism markers.

Growing resistant wheat (Triticum aestivum L) varieties is an important strategy for the control of leaf rust, caused by Puccinia triticina Eriks. This study sought to identify the chromosomal location and effects of leaf rust resistance loci in five Canadian spring wheat cultivars. The parents and doubled haploid lines of crosses Carberry/AC Cadillac, Carberry/Vesper, Vesper/Lillian, Vesper/Stettler and Stettler/Red Fife were assessed for leaf rust severity and infection response in field nurseries in Canada near Swift Current, SK from 2013 to 2015, Morden, MB from 2015 to 2017 and Brandon, MB in 2016, and in New Zealand near Lincoln in 2014. The populations were genotyped with the 90K Infinium iSelect assay and quantitative trait loci (QTL) analysis was performed. A high density consensus map generated based on 14 doubled haploid populations and integrating SNP and SSR markers was used to compare QTL identified in different populations. AC Cadillac contributed QTL on chromosomes 2A, 3B and 7B (2 loci), Carberry on 1A, 2B (2 loci), 2D, 4B (2 loci), 5A, 6A, 7A and 7D, Lillian on 4A and 7D, Stettler on 2D and 6B, Vesper on 1B, 1D, 2A, 6B and 7B (2 loci), and Red Fife on 7A and 7B. Lillian contributed to a novel locus QLr.spa-4A, and similarly Carberry at QLr.spa-5A. The discovery of novel leaf rust resistance QTL QLr.spa-4A and QLr.spa-5A, and several others in contemporary Canada Western Red Spring wheat varieties is a tremendous addition to our present knowledge of resistance gene deployment in breeding. Carberry demonstrated substantial stacking of genes which could be supplemented with the genes identified in other cultivars with the expectation of increasing efficacy of resistance to leaf rust and longevity with little risk of linkage drag.

Mapping of Stripe Rust and Leaf Rust Resistance Quantitative Trait Loci in the Chinese Spring Wheat Line Mianyang351-15.

Stripe rust and leaf rust cause wheat yield losses of up to 70% worldwide. The employment of resistant cultivars is the major method to reduce losses from these diseases. The objective of this study was to detect quantitative trait loci (QTL) for stripe rust and leaf rust resistance in 150 F6 recombinant inbred lines (RIL) derived from a cross between Mianyang351-15 and Zhengzhou 5389. Both parents and the RIL population were genotyped with the Wheat55K single nucleotide polymorphism (SNP) array and simple sequence repeat markers, and phenotyped for stripe rust severity at Mianyang in Sichuan Province and Baoding in Hebei Province, and for leaf rust severity at Zhoukou in Henan Province and at Baoding in 2014 to 2017 cropping seasons. Seven and four QTL all contributed from Mianyang351-15 were identified for resistance to stripe rust and leaf rust, respectively. Four of these QTL on chromosomes 1BL, 2AS, 2DS, and 7BL conferred resistance to both stripe rust and leaf rust. The QTL on 1BL, 2AS, and 7BL were identified as Lr46/Yr29, Lr37/Yr17, and Lr68, respectively. QYr.hbau-2DS/QLr.hbau-2DS was detected at similar positions to previously reported loci. QYr.hbau-1DL, QYr.hbau-3AS, and QYr.hbau-3DL are likely to be new. Combined effects of QTL in the RIL population indicated RIL combining all QTL had the highest resistance level compared with those of lower numbers or no QTL. These QTL, with their closely linked SNP markers, are applicable for marker-assisted breeding and candidate gene discovery.

Cultivar, planting date and weather linked to wheat leaf rust development

During four growing seasons (2013–2017), 282 leaf rust progress curves were characterized across experimental plots according to a number of climate-crop-disease variables in Kermanshah province, Iran. Leaf rust severity differed significantly between levels of cultivar, planting date, sampling time and year factors. Area under disease progress curve (AUDPC) based on disease severity was ranked using Kruskal–Wallis one-way ANOVA. H-test comparison between two disease-onset levels indicated lower mean AUDPC value for late disease onset than that for early disease onset. Highest and lowest AUDPC values were obtained in spring 2016 and 2015, respectively. According to principal component analysis, three principal components accounting for 73% of data variance verified dependence of leaf rust intensity on air temperature and wetness, cultivar resistance, date of disease onset, wheat maturity, and planting date. Based on principal component regression model, disease-onset and maturity date, mean 6-monthly temperature, number of days with minimum temperatures within the range of 5–25 °C and maximum RH > 60%, resistance index, and planting date justified 74% of variability in AUDPC dataset. These findings recommend involvement of cultivar resistance, dates of wheat maturity and planting along with weather predictors in wheat-leaf-rust studies to increase prediction value of future models, durability of host resistance to disease, and sustainability of disease control methods.

Weather‐data‐based model: an approach for forecasting leaf and stripe rust on winter wheat

AbstractClassification and regression trees (CARTs) for data analysis, an hourly weather dataset, and a 3 year field incidence and severity dataset of winter wheat rust were integrated to forecast pathogens’ presence/absence. The field dataset of incidence and severity was collected for three production cycles. Measured records of 88 Automatic Meteorological Stations and the indirect weather dataset generated in the Weather Research and Forecasting environment interpolated to each Automatic Meteorological Station location were analysed in the Python ecosystem. The focal point of the analysis was the severity of the disease. The analysis of direct weather data revealed the association of leaf rust severity with a night temperature of <14.25°C and global radiation of <521.67 W·m–2, while the estimated dataset showed that its severity is better explained by the dew point temperature of <13.7°C and a mean temperature of <19.06°C. The direct dataset also indicated that stripe rust severity was associated with relative humidity of <88.73%, global radiation of <597.39 W·m–2 and dew point temperature of <16.09°C, whereas the estimated data revealed that pathogen severity is better explained by a model composed of a dew point temperature of <14.6°C, night temperature of <20.4°C and a maximum temperature of <27.9°C. The severity and intensity analysis indicated the pathogen's preference for non‐dry ambient conditions and the preference of stripe rust pathogen for humid and warmer temperatures than leaf rust. The weather thresholds of both pathogens, and CART analysis, unveiled that winter wheat rust can be forecasted. This constitutes the foundation of a more efficient extension programme based on the internet of things.

Prediction of leaf rust severity and yield loss in wheat based on environmental factors

Six commercial bread wheat (Triticum aestivum L.) cultivars were evaluated against leaf rust (Puccinia triticina) at two different locations in Egypt during three successive growing seasons, i.e., 2016/2017, 2017/2018 and 2018/2019. Correlation between eight weekly environmental factors: solar radiation, total precipitation, average wind speed, maximum wind speed, minimum air temperature, maximum air temperature, minimum relative humidity and maximum relative humidity to leaf rust severity (%) and yield losses (%), was determined using stepwise regression analysis. Predictive models for each tested cultivar for final leaf rust severity (%) and yield losses using environmental data were determined. Generally, maximum relative humidity was positively correlated with final leaf rust severity (%). Significant correlation between yield losses (%) and the two factors, i.e., final leaf rust severity (%) and maximum relative humidity, was also found in this study. Meanwhile, negative correlation was found between final leaf rust severity (%) and yield losses (%) and the two environmental factors, i.e., solar radiation and minimum relative humidity. The effectiveness of tested models was estimated by using R2 values for all models, and these models were validated to predict leaf rust severity (%) and yield loss.

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.

Exome association analysis sheds light onto leaf rust (Puccinia triticina) resistance genes currently used in wheat breeding (Triticum aestivum L.).

SummaryResistance breeding is crucial for a sustainable control of leaf rust (Puccinia triticina) in wheat (Triticum aestivum L.) while directly targeting functional variants is the Holy Grail for efficient marker‐assisted selection and map‐based cloning. We assessed the limits and prospects of exome association analysis for severity of leaf rust in a large hybrid wheat population of 1574 single‐crosses plus their 133 parents. After imputation and quality control, exome sequencing revealed 202 875 single‐nucleotide polymorphisms (SNPs) covering 19.7% of the high‐confidence annotated gene space. We performed intensive data mining and found significant associations for 2171 SNPs corresponding to 50 different loci. Some of these associations mapped in the proximity of the already known resistance genes Lr21, Lr34‐B, Lr1 and Lr10, while other associated genomic regions, such as those on chromosomes 1A and 3D, harboured several annotated genes putatively involved in resistance. Validation with an independent population helped to narrow down the list of putative resistance genes that should be targeted by fine‐mapping. We expect that the proposed strategy of intensive data mining coupled with validation will significantly influence research in plant genetics and breeding.

QTL Mapping of Adult-Plant Resistance to Leaf and Stripe Rust in Wheat Cross SW 8588/Thatcher using the Wheat 55K SNP Array.

Wheat leaf rust (caused by Puccinia triticina) and stripe rust (caused by Puccinia striiformis f. sp. tritici) cause large production losses in many regions of the world. The objective of this study was to identify quantitative trait loci (QTL) for resistance to leaf rust and stripe rust in a recombinant inbred line population derived from a cross between wheat cultivars SW 8588 and Thatcher. The population and parents were genotyped with the Wheat 55K SNP Array and SSR markers and phenotyped for leaf rust severity at Zhoukou in Henan Province and Baoding in Hebei Province. Stripe rust responses were also evaluated at Chengdu in Sichuan Province, and at Baoding. Seven and six QTL were detected for resistance to leaf rust and stripe rust, respectively. Four QTL on chromosomes 1BL, 2AS, 5AL, and 7BL conferred resistance to both rusts. The QTL on 1BL and 2AS were identified as Lr46/Yr29 and Lr37/Yr17, respectively. QLr.hebau-2DS from Thatcher, identified as Lr22b that was previously thought to be ineffective in China, contributed a large effect for leaf rust resistance. QLr.hebau-5AL/QYr.hebau-5AL, QLr.hebau-3BL, QLr.hebau-6DS, QYr.hebau-4BS, and QYr.hebau-6DS are likely to be new QTL, but require further validation. Kompetitive allele-specific PCR (KASP) markers for QLr.hebau-2DS and QLr.hebau-5AL/QYr.hebau-5AL were successfully developed and validated in a diverse wheat panel from Sichuan Province, indicating their usefulness under different genetic backgrounds. These QTL and their closely linked SNP and SSR markers will be useful for fine mapping, candidate gene discovery, and marker-assisted selection in breeding for durable resistance to both leaf and stripe rusts.

Mapping of Genetic Loci Conferring Resistance to Leaf Rust From Three Globally Resistant Durum Wheat Sources.

Genetic resistance in the host plant is the most economical and environmentally friendly strategy for controlling wheat leaf rust, caused by Puccinia triticina Eriks. The durum wheat lines Gaza (Middle East), Arnacoris (France) and Saragolla (Italy) express high levels of resistance to the Mexican races of P. triticina. Three recombinant inbred line (RIL) populations, derived from crosses of each of these resistance sources to the susceptible line ATRED #2, were evaluated for leaf rust reactions at CIMMYT’s leaf rust nurseries in Mexico. Genetic analyses of host reactions suggested oligogenic control of resistance in all populations. The F8 RILs from each cross were genotyped using the Illumina iSelect 90K array, and high-density genetic maps were constructed for each population. Using composite interval mapping, a total of seven quantitative trait loci (QTL) that provide resistance to leaf rust were identified. Two QTL designated as QLr.usw-6BS and QLr.usw-6BL were identified on chromosome 6B in Gaza, which explained up to 78.5% and 21.3% of the observed leaf rust severity variance, respectively. A major QTL designated as QLr.usw-7BL was detected on the long arm of chromosome 7B in Arnacoris, which accounted for up to 65.9% of the disease severity variance. Arnacoris also carried a minor QTL on chromosome 1BL, designated as QLr.usw-1BL.1 that explained up to 17.7% of the phenotypic variance. Three QTL conferred leaf rust resistance in Saragolla, namely QLr.usw-2BS, QLr.usw-3B, and QLr.usw-1BL.2, which accounted for up to 42.3, 9.4, and 7.1% of the phenotypic variance, respectively. Markers flanking each QTL were physically mapped against the durum wheat reference sequence and candidate genes involved in disease resistance were identified within the QTL intervals. The QTL identified in this study and their closely linked markers are useful resources for gene pyramiding and breeding for durable leaf rust resistance in durum wheat.

Response of wheat genotypes against leaf rust (Puccinia triticina) under field conditions

Leaf rust occurs worldwide wherever wheat is grown. The current research was planned to evaluate the response of 37 wheat (Triticum aestivum) genotypes against leaf rust resistance under field conditions during crop season 2017-18.These genotypes were sown in augmented design with two meter long line sowing method with 30 cm row to row distance at research area of Agricultural Biotechnology Research Institute (ABRI), Ayub Agricultural Research Institute (AARI), Faisalabad, Pakistan. After every five genotypes, a line of rust spreader “Morocco” was sown. Moreover, the trial was also surrounded by planting two rows of spreader to increase the inoculum pressure. Data was recorded on the basis of leaf rust severity scale. Leaf rust severity response was variable among tested genotypes. Out of thirty-seven genotypes, five wheat lines were immune (no disease symptoms) i.e. 17BT007, 17BT013, 16BT008, 16BT010 and 16BT011. Seven lines were found to be resistant with AUDPC vales ranged 1-199. Response of ten lines was moderately resistant while five lines were categorized as moderately susceptible. Ten genotypes exhibited susceptible response against leaf rust with more than 600 AUDPC value. High values above 600 of AUDPC showed greater incidence of leaf rust on wheat plants while lower AUDPC values indicated resistance to leaf rust. Present research provided the resistant wheat lines to the breeders to incorporate them in their breeding program against leaf rust.

Molecular markers and phenotypic characterization of adult plant resistance genes Lr 34, Lr 46, Lr 67 and Lr 68 and their association with partial resistance to leaf rust in wheat

Thirty-nine wheat genotypes were studied to estimate their partial resistance levels to leaf rust at Behira governortae during three growing seasons, i.e. 2016/2017, 2017/2018 and 2018/2019. In these genotypes, partial resistance was characterized using final leaf rust severity (FRS %) and area under disease progress curve (AUDPC). Of the tested genotypes, only three wheat varieties; Giza 171, Misr 3 and Sohag 5 showed complete resistance. Further, 28 of the 39 genotypes had partial resistance as they revealed low and/or moderate values of FRS (%) and AUDPC (not exceeding 30% and 300, respectively). The other eight varieties were fast rusting, as they displayed the maximum values of FRS (%) and AUDPC. The four monogenic lines; Lr 34, Lr 46, Lr 67 and Lr 68 were identified in the wheat varieties using linked molecular markers; csLV34, Xgwm259, CFD71 and csGSR. Phenotypic results of the wheat varieties were confirmed by molecular marker analysis.

Saepo Modi and Correlation among Statistical Methods for Measuring of Phenotypic Stability

A stabile phenotype is desired. Many statistical methods are available to measure stability. So far, the choice of parameter of stability depended on the perception on the interaction of genotype and environment or ease of counting. The goal of this research was to study correlation among stability parameters. In total of 16 stability parameters were used in this research. Saepo modi (SMsp) as a stability parameter was also used. Branch rust incidence, leaf rust incidence, and leaf rust severity on Arabica coffee were used as variables. This research result showed that none of the parameters of stability correlated significantly with all parameter of stability. It coud be concluded that if someone want to use only one stability parameter, it is preffered to make use of regression and deviation from regression (D2i). In the case a researcher needs to use several of parameters of stability, Saepo modi (SMsp) might be exercised.

Identification and mapping of two adult plant leaf rust resistance genes in durum wheat

The International Maize and Wheat Improvement Center (CIMMYT)-derived durum wheat line Quetru is moderately resistant to leaf rust and displays disease severities of 15–30% at the adult plant stage. Atil C2000 is moderately susceptible to leaf rust at adult plant stage and displays severities of 20–60%. These two durum wheats were crossed with the susceptible line Atred#1, and the respective recombinant inbred line populations were phenotyped for resistance to leaf rust in field trials in four environments in Mexico. The phenotypic segregation in the Atred#1 × Atil C2000 population was attributed to the pleiotropic adult plant resistance (APR) gene Lr46 based on the closest marker cslv46G22 located within 1.4 cM. Lr46 reduced leaf rust severity by 19.6–35.5%, and it was also identified in the Atred#1 × Quetru population, where it reduced leaf rust severity by 28.5–57.7% depending on the environment. We also identified a putatively novel, race-specific APR gene LrQ in Quetru that is located on the Chromosome 6BL and flanked by SNP markers AX-95144243 and AX-95155193. These two markers have been converted into kompetitive allele–specific PCR (KASP) markers and validated in the population. LrQ was ineffective at the seedling stage but reduced leaf rust severity by 37.3% on average over four field trials. The combination of LrQ and Lr46 resulted in significantly reduced leaf rust severity in the field and could be used to breed improved durum wheat varieties.

Resistance Variability of Arabica Coffee Genotypes (Coffea arabica L.) to Leaf Rust Disease (Hemileia vastatrix)

<p>Coffee leaf rust disease (<em>Hemileia vastatrix</em>) causes large damage to Arabica coffee plantation in Asia, Africa, and America. In Indonesia, particularly in North Sumatra, the resistance level of Arabica coffee genotypes is still unknown. The objective of this research was to determine the resistance variability of Arabica coffee genotypes to leaf rust disease and its relation to leaf morphology. A total of 84 genotypes grown in North Sumatra were selected in November 2015 and 2016, and December 2017 using a nested design. Data were analyzed using nested design, correlation, stepwise regression, and cluster hierarchy analysis. The result showed that the G56 genotype performed the most resistant to leaf rust disease, with a severity of 5.21%. The severity of leaf rust disease has high genotypic variation, low heritability, and high genetic advance. Leaf morphological ratios showed moderate to high genotypic variation and heritability. The severity of leaf rust (y) significantly correlated with the ratio of leaf length to leaf area (x<sub>1</sub>) and the ratio of leaf length to leaf width (x<sub>2</sub>) with the equation y = 2.04 + 62.48x<sub>1 </sub>- 3.95x<sub>2,</sub> and multiple correlation coefficients R = 0.470 **. By using the leaf rust severity and the two ratios in the cluster analysis, these 84 genotypes were grouped into five clusters. The result showed that several Arabica coffee genotypes with a high level of resistance to leaf rust disease are potential to be further developed.</p>

Mining of Indian wheat germplasm collection for adult plant resistance to leaf rust.

Leaf rust (Puccinia triticina Eriks.) is a fungal disease of wheat (Triticum spp.), which causes considerable yield loss. Adult plant resistance (APR) is one of the most sustainable approaches to control leaf rust. In this study, field-testing was carried out across ten different locations, followed by molecular screening, to detect the presence of APR genes, Lr34+, Lr46+, Lr67+ and Lr68 in Indian wheat germplasm. In field screening, 190 wheat accessions were selected from 6,319 accessions based on leaf tip necrosis (LTN), disease severity and the average coefficient of infection. Molecular screening revealed that 73% of the accessions possessed known APR genes either as single or as a combination of two or three genes. The occurrence of increased LTN intensity, decreased leaf rust severity and greater expression of APR genes were more in relatively cooler locations. In 52 lines, although the presence of the APR genes was not detected, it still displayed high levels of resistance. Furthermore, 49 accessions possessing either two or three APR genes were evaluated for stability across locations for grain yield. It emerged that eight accessions had wider adaptability. Resistance based on APR genes, in the background of high yielding cultivars, is expected to provide a high level of race non-specific resistance, which is durable.

Mapping and DNA marker development for Lr33 from the leaf rust resistant line KU168-2

A wheat accession from the Kyoto University Collection, KU168-2, was identified as carrying good resistance to leaf rust and stem rust. To analyze this resistance a doubled haploid (DH) population was produced from hybrids of the cross KU168-2 with the leaf rust susceptible line RL6071. The DH population, of 116 lines, was evaluated for leaf rust resistance in the greenhouse at the seedling and adult plant stages, and in three field environments. Significant effects for reduction in leaf rust severity in the field were found on chromosome 1BL, most likely Lr33, which was also identified in the seedling tests, and on 7DS, which was identified as Lr34 in greenhouse adult plant tests and confirmed with a predictive molecular marker. In field trials, both Lr33 and Lr34 reduced the severity of leaf rust, while the lines with both resistance genes showed additivity of resistance. Similar results were consistently found from 2003 to 2017 testing Thatcher near-isogenic lines with Lr33, Lr34, and Lr33 + Lr34. A genetic map of the Lr33 region was developed and linked SNP markers were converted to KASP markers for the selection of Lr33 in wheat breeding programs. Two additional seedling resistance genes were found, one originating from KU168-2 on 6AL, and one from RL6071 on 7BL, but these genes did not contribute to field resistance.

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 & Martins equation indicates a very high severity potential.