Academia.edu no longer supports Internet Explorer.
To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to upgrade your browser.
2021, INTED2021 Proceedings
…
18 pages
1 file
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Medicine Science | International Medical Journal, 2012
Aim of this study was to identify cause of death and related histological findings, and to find relationship between them in sudden natural deaths (SND) that were subjected to medicolegal autopsy. Totally 209 SND cases were enrolled in the study. After medicolegal autopsy, cause and manner of death were identified. A formula was formed to show the ratio of frequency of histological findings to cause of deaths in systems. By this formula, affected systems were compared. In SND cases, the ratio of extracardiac findings to extracardiac deaths was higher than that of cardiovascular findings to cardiovascular deaths (5.53 versus 2.00). We concluded that cardiovascular pathologies are still the most common in SND. The higher rate of extracardiac histological findings doesn t mean higher rate of SND due to extracardiac causes. Therefore, histological findings must be evaluated with great attention for preventing incorrect conclusions to identify causes of deaths in SND.
The Professional Medical Journal
Objectives: The purpose behind this study was to determine the pattern of the causes of death in adult males - a perspective on autopsy. Study Design: Cross sectional study. Period: 2015 to 2016. Setting: Peoples Medical College Hospital, Nawabshah, Shaheed Benazirabad, Sindh, Pakistan. Material and Methods: 73 male patients, whose autopsy were performed through a convenience non-purposive sampling technique to ascertain the causes of death among dead bodies brought at Peoples Medical College Hospital, Nawabshah, Shaheed Benazirabad, Sindh, Pakistan for the purpose of autopsy. Autopsy was performed with consent taken from the family members and hospital administration. Questionnaire was used to collect the limited relevant data and used SPSS version 17 for data entry and analysis. Results: Mean age of patients whom autopsy were performed was 37.12 years among them minimum age was 10 year and maximum age recorded was 75 years. Among all, 31 (42.46%) cases were from rural area while 4...
Eastern Green Neurosurgery
Background: The World Health Organization (WHO) has defined sudden unexpected death as a death, non-violent and not otherwise explained, occurring within 24 hours from the onset of symptoms. This study was performed with the objective to evaluate the different neurological causes of sudden and unexpected death. Methods and materials: this is a cross-sectional analytical study with non-probability consecutive sampling technique over the period of one year. Data were collected, and analyzed using SPSS 20. Data were presented in percentages, and stratifications were used to control the modifiers. Results: There were total 110 autopsies done during the period of one year for sudden and unexpected deaths, among which 19 (17.3%) were deaths due to neurological causes, where 17(89.5%) were males and 2(10.5%) were females. There were 68.43% deaths seen during cold weather. Smoking, alcohol and drug abuse all seems to have higher prevalence among the sudden death due to neurological cause. M...
2015
Sudden cardiac death (SCD) is the most important challenge of modern cardiology. As in present times it can be prevented and the knowl-edge of pathological mechanisms as well as the correlation between SCD and associated diseases and risk factors is crucial. There is a great geo-graphical variety in the incidence of SCD and ischemic heart disease (IHD) as its main under-lying cause with lower incidence of IHD and SCD episodes in Mediterranean countries. However, although the incidence of SCD in Spain is one of the lowest in the industrialized countries, a recent-ly published study has demonstrated that the incidence of atherosclerotic plaques in young people detected at autopsy is unexpectedly high.
Medicina Sportiva, 2009
Sudden cardiac death (SCD) is responsible for a considerable number of fatalities in the mountain environment. Victims are often middle aged men with risk factors for coronary artery disease (CAD). Deaths tend to occur during, or immediately after exercise and may be exacerbated by sympathetic stimulation triggered by factors such as anxiety, poor sleep, intercurrent infection, inadequate food intake and dehydration. Myocardial ischaemia, coronary artery spasm and the rupture or erosion of an atherosclerotic plaque have all been cited as potential causes for SCD in the mountain environment. Any strategy intent on reducing the risk of SCD will need to focus upon developing recommendations for those with CAD as well as the larger population who have risk factors for the disease. In addition to preventative strategies, popular ski centres and mountain resorts should also be capable of providing basic care for those who develop an acute coronary syndrome (ACS) and direct victims to appropriate treatment with the utmost urgency.
Background-Identifying persons at risk for sudden cardiac death (SCD) is challenging. A comprehensive evaluation may reveal clues about the clinical, anatomic, genetic and metabolic risk factors for SCD.
Transportation Research Part B-methodological, 2012
Currently, most intersection models embedded in macroscopic Dynamic Network Loading (DNL) models are not well suited for urban and regional applications. This is so because socalled internal intersection supply constraints, bounding flows due to crossing and merging conflicts inherent to the intersection itself, are missing. This paper discusses the problems that arise upon introducing such constraints, which result firstly from a lack of empirical knowledge on driver behavior at general intersections under varying conditions and the incompatibility of existing theories that describe this behavior with macroscopic DNL. A generic framework for the distribution of (internal) supply is adopted, which is based on the definition of priority parameters that describe the strength of each flow in the competition for a particular supply. Secondly, using this representation, it is shown that intersection modelseven under realistic behavioral assumptions and in simple configurations (i.e. without internal supply constraints)can produce non-unique flow patterns under identical boundary conditions. This solution non-uniqueness is thoroughly discussed and conceptual approaches on how it can be dealt with in the model are provided. Also the spatial modeling point of view is consideredas opposed to the more traditional point-like modeling. It is revealed that the undesirable model properties are not solvedbut rather enhancedwhen diverting from a point-like to a spatial modeling approach. Therefore, we see more merit in continuing the point-like approach for the future development of sophisticated intersection models. Necessary research steps along these lines are formulated.
2007
The fluorescence in situ hybridisation (FISH) technique with whole chromosome painting for chromosomes #1 and #4 was used to study the impact of air pollution containing higher concentrations of carcinogenic polycyclic aromatic hydrocarbons (c-PAHs) in three European cities, Prague (Czech Republic), Kosice (Slovakia) and Sofia (Bulgaria). In each site an exposed group was followed consisting of police officers or bus drivers who work usually through busy streets for at least 8 h, and a control group, who spent more than 90% of their daily time indoors. In Prague, a significant increase was observed in all the studied endpoints in the police officers compared to the control population (P<0.05).
The paper examines the taxation, private fixed domestic investment and economic growth nexus in Zimbabwe for the period 1998 to 2015 using Ordinarily Least Square regression. Private fixed investment decisions undertaken by firms and other economic agents are very critical for the economic growth. Levels of taxation affect production, consumption, and distribution of wealth in an economy. Taxation revenues can be utilised as a vital tool to: raise government revenue, enhance price stability, optimally allocate and distribute available resources, boost domestic savings, increase domestic investment as well as to accelerate the pace of economic growth.Taxation, domestic savings, public corruption and lagged GDP were found to be significant. Our results suggest that taxation revenue that are channelled to productive public expenditure such as roads, bridges, rail, energy, transport and other communication systems are likely to stimulate the productivity of private fixed domestic investment. The primary challenge for policy makers is devise tax rules that lowers tax evasion, reduce corruption, enhance domestic savings yet adequately protect the tax base whilst lessening the current heavy excess burden on firms.
RnRMarketResearch.com adds “Microscopic Polyangiitis (MPA) – Pipeline Review, H1 2015” to its store. This report provides comprehensive information on the therapeutic development for Microscopic Polyangiitis (MPA), complete with comparative analysis at various stages.
Introduction
Several tetraploid wheats (2n = 4x = 28) of the species Triticum turgidum L. are cultivated. Among them, durum wheat (T. turgidum subsp. durum (Desf.) Husn.) is the most important crop with a yearly acreage of about 16 million ha and a production of 37 million t [1]. Domesticated emmer wheat (T. turgidum subsp. dicoccon (Schrank) Thell.) and rivet or poulard wheat (T. turgidum L. subsp. turgidum) are also cultivated crops. Domesticated emmer wheat is a hulled grain wheat that was very important in the past, but today remains as a relict crop in isolated areas of Italy, Ethiopia, Iran, and India [2]. Rivet wheat, also a minor crop, is similar to durum wheat but the spike (lax and long, with rough awns that can fall off at maturity) and the kernel (naked when threshed, but round and soft) are different.
Rusts are important diseases in wheat since they are dynamic pathogens and affect wheat worldwide [3]. Leaf (or brown) rust is a foliar disease caused by the fungus Puccinia triticina Eriks. It is the most constant disease globally out of the three rusts diseases (yellow rust, leaf rust, and stem rust). It affects to bread wheat, durum wheat, and triticale. Although durum wheat was generally deemed more resistant to leaf rust compared to bread wheat, from 1998 to 2006 severe leaf rust outbreaks on durum wheat were recorded at many locations in southern Spain. Most durum wheat cultivars rendered susceptible at that time in Spain, with a few exceptions such as the Italian cultivar Colosseo [4]. That moment almost coincided with severe outbreaks in Mexico and many other parts of the world [5]. Since then, many resistant cultivars were released mostly from CIMMYT or from Italian breeding companies. Most resistant cultivars carried Lr14a gene or the closely linked QLr.ubo-7B.2 (present in Colosseo) located on chromosome 7BL [6]. Other resistant cultivars carry the complementary genes Lr27 + Lr31 (that originated from bread wheat but transferred to several durum wheat cultivars such as Jupare C2001, and LrCamayo (present in cultivar Camayo), but nonetheless, the resistant stock is scarce.
Two features are typical of the leaf rust of durum wheat compared to bread wheat leaf rust isolates. First, races that affect most of the world (except Ethiopia) have a similar virulence profile and, presumably, a common origin [7]. However, this fact does not prevent new virulent races from occurring by mutation and selection against the main Lr genes deployed in durum wheat [8]. Second, it is the existence of a sibling species called Puccinia tritici-duri V.-Bourgin, that was described first in Morocco, and have Anchusa azurea Mill. as alternate host. This species displays larger pustules than common leaf rust, with a rapid tendency to form telia on the same position of the pustule [9]. Most Lr genes present in durum cultivars does not activate the resistance when the plant is challenged by this leaf rust species.
Apart from the normal hypersensitive resistance based on single, major, and race specific Lr genes, another type of resistance called partial resistance (PR) has contrasting features. It is quantitative, race nonspecific (horizontal), and based on minor genes, although some of those genes show greater effect than others. The resistance is normally durable, i.e., it is effective for a long period of time in a prone environment to disease, in contrast with the hypersensitive resistance, with may be overcome when a new race develops a mutation in the avirulence loci [10]. Partial resistance to wheat leaf rust was first described in bread wheat [11,12], where several cultivars showed to possess fair levels of PR (Frontana, Parula, Pavon 76, etc.). Some genes for partial resistance have been characterized, as Lr34 and Lr46, and, interestingly, these genes have a pleiotropic effect, that is, they provided resistance to other diseases [13]. Although PR to rust was first defined in field experiments, displaying a typical "slow rusting" in the progress of the disease, the components of this resistance can be measured in greenhouse or growth chamber in monocyclic experiments. Therefore, parameters like the latency period (time between inoculation and the time at which 50% of the final number of pustules appeared) [14] or the uredinium size are well correlated with the slow rusting in the field. In durum wheat, works on PR to leaf rust in several cultivars (such as Planeta) demonstrated that uredinium size was the best predictor of partial resistance, followed by the latency period [15,16].
Landraces are characterized by a specific adaptation to the environmental conditions of the area of cultivation [17] where the selection of resistant genotypes in some populations is an adaptive response to the biotic stress caused by the pathogen. There are some examples of landraces as source of resistant genes to rust: the Levantine landrace Gaza carries Lr23 [18], while the Portuguese accessions AUS 26582 and AUS 26579 carries the Lr61 present in the cultivar Guayacán [19]. In durum wheat landraces coming from the Iberian Peninsula has been also found leaf rust resistance [20]. Additionally, landraces may have fair levels of partial resistance. Farmers (aided by natural selection) have made a selection against extreme rust susceptibility across seasons in rust prone areas [21,22].
The evaluation of landraces collections for rust response is a useful approach for exploring novel variation and determine their potential as sources for favourable alleles conferring resistance. However, the number of relevant accessions in genebank collections available to be evaluated is often substantially larger than the capacity of the evaluation project. An efficient strategy to mining genetic resource collections is to carefully screen core collections where the genetic diversity is maximized, and the number of accessions is lower than is normally required for evaluation to identify novel variation. A core collection of 94 genotypes comprising landraces of the three tetraploid subspecies is currently preserved in the CRF-INIA (Centro Nacional de Recursos Fitogenéticos, National Plant Genetic Resources Centre) at Alcalá de Henares (Madrid) [23]. Several studies have demonstrated the high genetic variability of these collections for different traits relevant for wheat improvement [24][25][26].
It has been reported that wheat landraces with the highest level of resistance to some diseases originated from sites where diseases pressure was high, due to environmental factors [21,27]. Therefore, the ecogeographic characterization of the landraces cultivation sites can be very useful in explaining the suitable eco-geography where the pathogen thrives and thus are likely to impose a selection pressure for the emergence of resistance genes. The relation between resistance expression in the evaluated accessions and the ecogeographic parameters of the collection site allow to detect novel variation in other populations originating from locations with an environmental profile similar to the collection sites of the reference set of accessions with known resistance. Different studies analysing the associations between ecogeographic variables and rust resistance in common wheat demonstrated a strong environmental component in the geographic distribution of rust resistance genes [28][29][30][31]. Nevertheless, few studies have focussed on leaf rust of durum wheat.
The objective of this work was to evaluate the resistance to several isolates of leaf rust in the Spanish core collection of tetraploid wheat and to relate the origin of the resistant landraces with local ecogeographical variables.
Materials and Methods
Plant Material
The Spanish core collection of tetraploid wheat used in the analysis of rust resistance at seedling stage in greenhouse comprised 94 landraces of three subspecies of the species Triticum turgidum L. (10 of domesticated emmer wheat, 32 of rivet wheat, and 52 of durum wheat). Four essays were carried out in seedlings, three to evaluate the hypersensitive resistance to leaf rust with three different isolates, and the other to characterize the partial resistance of the collection to one of the isolates. The cultivar Don Rafael was used as susceptible check, while cultivar Don Valentín (Lr27 + Lr31) was utilized as resistant check, and cultivar Planeta as partially resistant check.
Another set of 192 Spanish landraces of tetraploid wheat (14 of domesticated emmer wheat, 38 of rivet wheat, and 140 of durum wheat), which included the core collection, was evaluated at adult plant stage in field experiments. This set was representative of the entire collection of 552 accessions maintained at the CRF and was used as primary subset to select the core collection [32].
Fungal Material
The isolates of Puccinia triticina used in this study were Conil Don Jaime 13 (CDJ13) and Jerez Don José 15 (JDJ15), both collected from durum wheat fields in southern Spain, and Peralta García 14 (PG14), collected from common wheat in northern Spain. Inoculation on a Thatcher/Lr isolines differential set showed that the isolates were virulence/avirulence on the following Lr genes:
Experiment of Hypersensitive Resistance at Seedling Stage in the Greenhouse
Landraces of the core collection were sown in plastic trays of 60 × 40 cm in soil made of peat moss and sand (1:1 v./v.). In each tray, four plants of 16 landraces plus the susceptible and resistant check were grown in a greenhouse at Technical School of Agricultural Engineering (ETSIA, University of Seville, Seville, Spain). Inoculations were performed in two different experiments at two different plant seedling stages, first and fifth leaf (12 and 16 Zadoks scale) [33]. Plants were inoculated by dusting 4 mg of uredospores per tray mixed with talc powder (1:40 v./v.), which resulted in a deposition of about 70 spores/cm 2 . Leaves were laid and fixed on the soil with metallic hairpins. Inoculated plants were placed in an incubation compartment within the greenhouse at 18-20 • C, with darkness and humidity at saturation for 15 h. The next day, hairpins were removed from the leaves and plants were transferred back to their greenhouse compartment. At 13 days after inoculation, when the number of pustules in the susceptible check no longer increased, infection type was assessed in each leaf of the landraces, using the McNeal scale [34]. In most cases, infection type score agreed in all four leaves of each landrace. This scale is a 0-9, where infection type lower than 7 indicated a resistant or incompatible response in the landraces, while an infection type of 7 or more indicated a susceptible or compatible response.
Experiment of Partial Resistance at Seedling Stage in the Greenhouse
For this experiment, the 75 landraces that showed a high infection type (IT ≥ 7) when inoculated with isolate CDJ13 were sown again in plastic trays, but the resistant check was replaced by the partially resistant cultivar Planeta. Four first leaves of each landrace were inoculated this time using a settling tower to improve the uniformity of the inoculation. The length (L) and the width (W) of eight uredinia per leaf and genotype were measured with a binocular microscope. From these measures the surface of the uredinium, considered as an ellipse, was π/4 × L × W. This trait is highly correlated with partial resistance to leaf rust of durum wheat [15].
Leaf Rust Evaluation at Adult Plant Stage in the Field Experiments
Wheat landraces were tested for leaf rust in adult plant in field plots in 2007-2008 at Jerez de la Frontera (36 • 43 42" N, 6 • 09 46" W), a southern Spanish region prone to wheat rust disease [4]. The accessions were sown in an augmented design [35] in plots of 3 rows of 2.5 m length and 15 cm row spacing. Two durum wheat cultivars widely cultivated in the country, Simeto and Vitrón, were included in each block as checks. Both cultivars are susceptible to the leaf rust races developed after 1998. Field infection was natural and leaf rust severity was assessed following the modified Cobb scale [36], expressed as a proportion of foliar surface covered by pustules with respect to the total plant (from 0 to 100%). Accessions with leaf rust severity from 0 to 10% were considered resistant, since hypersensitive resistance usually results in fewer and smaller pustules that reduce greatly the severity [3], and those with severity higher than 10% were regarded as susceptible.
Agronomic Characterisation
Four qualitative agromorphological traits (growth habit, spike density, glume hairiness, and seed colour) were obtained from a previous study [32] carried out during the season 2006-2007 at the centre of Spain (Alcala de Henares, Madrid). Three quantitative agromorphological traits (days to heading and to maturity, and plant height) were obtained from that study and also recorded from the rust resistance field experiment in 2007-2008. All traits were evaluated according to the International Board of Plant Genetic Resources (IBPGR) from five different plants in each accession (Table S1).
Table 1
Confusion matrix (2 × 2 contingency table).
Ecogeographic Characterisation
Ninety-one accessions of the core collection and 177 accessions of the whole set evaluated in field plots were assigned to one of the nine agroecological zones for durum wheat defined on the basis of historical yield records and province of origin of the landrace [32]. Geographic coordinates (latitude, longitude and altitude) of the collection site of each landrace were obtained for 54 accessions of the core collection and 84 accessions evaluated in the field trial from the passport data of each accession (http://webx.inia.es/web_inventario_naci onal/Introduccioneng.asp, accessed on 23 March 2021). The accuracy of the geographic coordinates was checked with Google Earth (www.google.com/earth/index.html, accessed on 23 March 2021). Data on 75 ecogeographic variables classified into three ecogeographical components were gathered: bioclimatic variables (67), geophysic variables (3) and edaphic variables (5) (see Table S2). The bioclimatic variables (1950-2000 period) were related to temperature and rainfall, including some indexes which analysed the relationships between both climatic effects. The geophysic variables were related to solar radiation (northness, eastness, and elevation), and the edaphic parameters were related to the physical and/or chemical conditions of the soil (pH, bulk density, and clay and sand content). The values of the ecogeographic variables were extracted for each collection site from raster layers with a 2.
Table 2
Number of resistant accessions (IT < 7) to specific isolates of leaf rust at the seedling stage in the core collection of tetraploid wheat.
Data Analyses
For qualitative traits, significant differences between the frequencies in the rust resistant and susceptible groups were checked by chi-squared test (p-value < 0.05). For quantitative variables, a homogeneity test (Levene's test) for variances and a t-test for means (p-value < 0.05) were used to compare the resistant and susceptible groups. For those variables deviated from equality of variances, the nonparametric Kruskal and Wallis test was used [38]. Relationships between variables were examined using Pearson correlation coefficient (p < 0.05).
For the core collection evaluated at the seedling stage, a predictive model was elaborated for each isolate with the random forest (RF) clustering algorithm using the bioclimatic data (explanatory variables) and the leaf rust resistant/susceptible classes (dependent binary variable). This procedure differs from standard tree classifier in that it "grows" many classification trees in the process, leading to higher classification accuracy than other classifiers [39]. The number of variables in the random subset at each split node (mtry) were optimized for each model by monitoring the magnitude of the mean square prediction error (rate of classification error) observed in the out-of-bag (OOB) set; that is, the ability of each iteration to correctly classify an unknown accession as resistant or susceptible. The number of trees in the forest (ntree) was 1000 for all the models.
Two "test" sets of accessions screened for adult plant resistance in field plots were used to evaluate the prediction performance of the model obtained with the RF approach: one including all the accessions (set 1), and other with accessions not included to build the model (set 2). The model was supplied with the bioclimatic data of the two sets of accessions and the results of the predictions were validated by the disease evaluation scores recorded in the field tests. All the accessions of set 2 were susceptible at the adult stage in the field trial, so a third set (set 3) which included five accessions from the core collection, resistant under field conditions, was also used to evaluate the model. No model was constructed for the common wheat isolate since this model was not possible to be evaluated with data from field experiments.
The agreement between the models' predictions and the disease scores in the field plots were quantified with the Kappa parameters: sensitivity, specificity, Kappa coefficient, and accuracy. These parameters were derived from the 2 × 2 contingency table (Table 1). Sensitivity, defined by a/(a + c), and specificity, defined by d/(b + d), are indicators of the model's ability to correctly classify observations as either resistant or susceptible. The higher the values of sensitivity and specificity, the lower the error and thus the better the discriminating power of the model. The Kappa coefficient was used to assess improvement over chance and measures the specific agreement in the confusion matrix table. Thus, a high value is an indication that the models performance were adequate for prediction purposes [40]. A value of Kappa below 0.4 was an indication of poor agreement and a value of 0.4 and above was an indication of good agreement [41]. The overall correct classification was defined by (a + d)/n. The RF analysis provides a ranking of the most important variables influencing the resistant/susceptible classification, placing variables with a higher mean decrease in accuracy in the first positions. The variables in the top 30 variables of the ranking with Pearson correlation coefficient r > |0.50| and p < 0.05 were considered correlated variables. Statistical analyses were performed with the software R version 3.6.3 and Infostat version 6.12 software.
Results
Leaf Rust Resistance of the Core Collection at Seedling Stage in the Greenhouse
Correlations between Disease Parameters
The Spanish core collection of 94 accessions of the three T. turgidum subspecies, domesticated emmer wheat (10 accessions), rivet wheat (32 accessions), and durum wheat (52 accessions) were evaluated for leaf rust resistance to the rust isolates CDJ13, JDJ15 and PG14 at first and fifth leaf stages in greenhouse tests. Three parameters were tested: the infection type (IT), disease severity (DS) and leaf necrosis (LN) ( Table S3). Correlation analyses detected significant correlations between the first and fifth leaf scores for the three parameters within each isolate ( Figure 1). DS was positively and negatively correlated with IT and LN, respectively, in all the isolates. Between isolates, the highest correlations were between CDJ13 and JDJ15 for the three parameters assessed.
Table 3
Figure 1
Pearson correlations between the disease parameters infection type (IT), disease severity (DS) and leaf necrosis (LN) assessed for each isolate Conil Don Jaime 13 (CDJ13), Jerez Don José 15 (JDJ15) and Peralta García 14 (PG14). The number 1 and 5 after the disease parameter indicated first and fifth leaf, respectively. Coefficients > |0.2| are significant (p < 0.05).
Identification of Resistant Accessions to Leaf Rust
Resistant accessions to each isolate were identify by their IT of leaf rust at the fifth leaf stage. Although first and fifth leaf scores were related, the fifth leaf response was better correlated with the adult plant response since several adult plant genes are ex-
Resistant accessions to each isolate were identify by their IT of leaf rust at the fifth leaf stage. Although first and fifth leaf scores were related, the fifth leaf response was better correlated with the adult plant response since several adult plant genes are expressed since the fifth leaf rust stage [42]. Thus, those accessions with IT values at fifth leaf lower than 7 were considered resistant to the corresponding isolate. The number of susceptible accessions to the leaf rust isolates CDJ13 and JDJ15 was higher than the number of resistant accessions, whereas the latter was predominant for PG14 (Table 2). Seven durum landraces, six rivet and five domesticated emmer wheat accessions of the core collection presented simultaneous resistance against the three leaf rust isolates. The subspecies showed significant differences in the number of resistant accessions within each isolate (p = 0.0013, 0.02 and 0.0008 for CDJ13, JDJ15 and PG14, respectively). A higher frequency of resistant accessions to CDJ13 and JDJ15 occurred among the accessions of domesticated emmer wheat than among durum and rivet wheat accessions ( Table 2). For PG14, both domesticated emmer and durum wheat included a higher frequency of resistant accessions than rivet wheat. Furthermore, all the analysed domesticated emmer wheat accessions were resistant to PG14.
Relations between Seedling Resistance and Agronomic Traits
The relationship between agromorphological traits and disease resistance was evaluated for durum and rivet wheat. Domesticated emmer wheat was not included in the analyses because this subspecies has a typical agrotype very different from those of the other two subspecies. For the qualitative morphological traits (Table S1), resistant accessions to CDJ13 and JDJ15 showed a higher frequency of red seeds than white seeds, while an opposite tendency was detected for the susceptible group (p < 0.01) ( Figure 2). None of the morphological characters growth habit, spike density and glume hairiness showed significant associations with leaf rust resistance to any of the three isolates.
Figure 2
Seed color frequency in resistant and susceptible accessions to (a) Conil Don Jaime 13 and (b) Jerez Don José 15 isolates at seedling stage for durum and rivet wheat of the core collection. Agriculture 2021, 11, x FOR PEER REVIEW 9 of 19
For the quantitative agronomic traits, days to heading and maturity, and plant height (Table S1), the only significant difference detected was that resistant accessions to CDJ13 had a higher number of days to heading than those recorded as susceptible (176 days vs. 172 days, p = 0.0075).
The relationship between agromorphological traits and disease resistance was evaluated for durum and rivet wheat. Domesticated emmer wheat was not included in the analyses because this subspecies has a typical agrotype very different from those of the other two subspecies. For the qualitative morphological traits (Table S1), resistant accessions to CDJ13 and JDJ15 showed a higher frequency of red seeds than white seeds, while an opposite tendency was detected for the susceptible group (p < 0.01) ( Figure 2). None of the morphological characters growth habit, spike density and glume hairiness showed significant associations with leaf rust resistance to any of the three isolates. For the quantitative agronomic traits, days to heading and maturity, and plant height (Table S1), the only significant difference detected was that resistant accessions to CDJ13 had a higher number of days to heading than those recorded as susceptible (176 days vs. 172 days, p = 0.0075).
Relations between Seedling Resistance and Ecogeographic Variables of the Collection Site
The association of evaluation data for leaf rust resistance with the environmental conditions of the collection sites of the assessed accessions can help to identify environments that are likely to impose selection pressure for the emergence of resistance genes. In the present study, domesticated emmer wheat was not included in the analyses to avoid possible deviations, since this subspecies is traditionally cultivated in a unique ecogeographic region in the north of the country, where durum wheat is not usually cultivated. In contrast, durum and rivet wheat growth sites are more widely distributed across the country. Most of the sites of the durum and rivet wheat accessions were ascribed to one of the nine agroecological zones in Spain [32]. Although some zones were represented by a low number of accessions in the present study, for CDJ13 and JDJ15 the highest frequency of resistant accessions was found in the eastern zone of Spain (Zone 8) ( Figure 3).
Figure 3
Maximum temperature of hottest month (−) December precipitation (+) August maximum temperature (−) Annual precipitation (+) July mean temperature (−) January precipitation (+) Precipitation of coldest quarter (+) February precipitation (+) 1 The (+) or (−) indicates the associations of high or low values of the variable with the resistant accessions. The variables that were also significant different between resistant and susceptible accessions in adult plants in the field are underlined. CDJ13 = Conil Don Jaime 13, JDJ15 = Jerez Don José 15.
The association of evaluation data for leaf rust resistance with the environmental conditions of the collection sites of the assessed accessions can help to identify environments that are likely to impose selection pressure for the emergence of resistance genes. In the present study, domesticated emmer wheat was not included in the analyses to avoid possible deviations, since this subspecies is traditionally cultivated in a unique ecogeographic region in the north of the country, where durum wheat is not usually cultivated. In contrast, durum and rivet wheat growth sites are more widely distributed across the country. Most of the sites of the durum and rivet wheat accessions were ascribed to one of the nine agroecological zones in Spain [32]. Although some zones were represented by a low number of accessions in the present study, for CDJ13 and JDJ15 the highest frequency of resistant accessions was found in the eastern zone of Spain (Zone 8) ( Figure 3). Relationships between disease resistance and 75 ecogeographic variables of the collection site in Spain were analysed for durum and rivet wheat (Table S2). Resistant and susceptible accessions showed significant differences for the ecogeographic variables related to their collection site for the isolates CDJ13 and JDJ15, but none was significant for the geophysic or edaphic variables (Tables 3 and S4). The highest number of differences between both resistant and susceptible groups was detected for JDJ15. For that isolate, both bioclimatic thermal and hydric variables showed contrasting differences. In general, resistant accessions came from areas with more uniform temperatures, lower maximum temperatures in the hottest period, and higher precipitation in the coldest season. Resistant accessions for CDJ13 usually came from zones with higher isothermality. Table 3. Ecogeographic variables ordered according to their significant differences (p < 0.05) be- Relationships between disease resistance and 75 ecogeographic variables of the collection site in Spain were analysed for durum and rivet wheat (Table S2). Resistant and susceptible accessions showed significant differences for the ecogeographic variables related to their collection site for the isolates CDJ13 and JDJ15, but none was significant for the geophysic or edaphic variables ( Table 3 and Table S4). The highest number of differences between both resistant and susceptible groups was detected for JDJ15. For that isolate, both bioclimatic thermal and hydric variables showed contrasting differences. In general, resistant accessions came from areas with more uniform temperatures, lower maximum temperatures in the hottest period, and higher precipitation in the coldest season. Resistant accessions for CDJ13 usually came from zones with higher isothermality. Table 3. Ecogeographic variables ordered according to their significant differences (p < 0.05) between resistant and susceptible accessions at seedling stage for the durum and rivet wheat of the core collection. The classification model obtained with the Random Forest approach for both durum wheat isolates indicated that thermal variables were more relevant in the model than hydric variables (Table S5). The identification of the most significant no correlated variables confirmed the influence of the temperature uniformity for both isolates, and autumn precipitation for JDJ15 (Table 4).
Table 5
Accuracy of the random forest classification of different sets of accessions assessed at adult plant stage in the field experiments.
Table 4
The most significant bioclimatic variables not correlated in the top 30 variables selected according to the mean decrease accuracy of the random forest approach for durum and rivet wheat within each isolate at seedling stage.
Leaf rust Resistance at Adult Plant Stage in the Field Experiments
A total of 192 tetraploid landraces (including the core collection) were tested for leaf rust severity in field plots in the south of Spain (Table S6). The two check cultivars, Simeto and Vitrón, showed a high susceptibility, with a leaf rust severity of 90%. Significant correlations were obtained between disease severity in the field (adult plant stage) and the IT values assessed for the landraces at the seedling stage for CDJ13 (r = 0.55, p< 0.0001) and JDJ15 (r = 0.60, p < 0.0001). A lower correlation was obtained for the common wheat isolate PG14 (r = 0.19, p = 0.05) ( Figure S1).
Table 6
The three subspecies showed no significant differences in the number of resistant accessions (severity values lower than 10%) at the adult plant stage. However, significant differences for the severity level, which measured the foliar surface percentage covered by uredinia, existed among the subspecies (p < 0.0001); domesticated emmer wheat having the lowest values (40.7%), rivet wheat occupied an intermediate position (58.2%), and durum having the highest values (67.8%).
Similarly, to the results at seedling stage, resistant accessions of durum and rivet wheat had a higher frequency of red seeds (63%) than those being susceptible (26%) (p = 0.02). For these two subspecies, no significant differences were found among the agroecological zones, probably due to the low number of resistant accessions, but the associations with the ecogeographic variables indicated that accessions from areas with more stable and uniform temperatures, and more precipitation in October showed generally low severity values ( Table 3 and Table S7).
The classification models obtained for the two durum wheat isolates with the seedling tests were used to predict which accessions might be resistant or susceptible at the adult plant stage. All the accuracy parameters indicated a good agreement between predictions and score data in the field plots for the three sets of accessions evaluated ( Table 5). Some coefficients could not be calculated for set 2, which included only accessions not used to build the model, because all the accessions were susceptible at the adult stage. Both models had the same sensitivity for sets 1 and 3 (both identified 4 of the 5 resistant accessions in the field trial), although the model obtained for CDJ13 showed a better predictive power when all the accessions were used (set 1).
Partial Resistance to Leaf Rust at Seedling Stage in the Greenhouse
Partial resistance to CDJ13 was assessed in 74 susceptible accessions (IT ≥ 7) by measuring the uredinium size (Table S8). One accession of domesticated emmer wheat (BGE048901) showed a significant lower uredinium size (UrS = 0.059 mm 2 ) than the partially resistant check "Planeta" (UrS = 0.087 mm 2 ). Domesticated emmer wheat also displayed a lower uredinium size than rivet and durum wheat (Figure 4), indicating that domesticated emmer wheat accessions manifested a higher level of partial resistance.
Table 8
Figure 4
Mean values of uredinium size (UrS) of leaf rust at seedling stage for the three subspecies of T. turgidum. Means with different letters are significantly different at p = 0.05.
Partial resistance to CDJ13 was assessed in 74 susceptible accessions (IT ≥ 7) by measuring the uredinium size (Table S8). One accession of domesticated emmer wheat (BGE048901) showed a significant lower uredinium size (UrS = 0.059 mm 2 ) than the partially resistant check "Planeta" (UrS = 0.087 mm 2 ). Domesticated emmer wheat also displayed a lower uredinium size than rivet and durum wheat (Figure 4), indicating that domesticated emmer wheat accessions manifested a higher level of partial resistance. Correlations between agromorphological traits and uredinium size were not significant, except for days to heading which showed a negative correlation with UrS (p = 0.02). Correlation analyses performed separately for each subspecies detected that UrS was negatively correlated with days to maturity (p = 0.05) and positively correlated with growth Correlations between agromorphological traits and uredinium size were not significant, except for days to heading which showed a negative correlation with UrS (p = 0.02). Correlation analyses performed separately for each subspecies detected that UrS was negatively correlated with days to maturity (p = 0.05) and positively correlated with growth habit (p = 0.02) only in rivet wheat.
Separate analyses for each subspecies revealed no significant correlations between UrS and the ecogeographic characteristics of the collection site. In contrast, the combined analyses for the three subspecies indicated that partial resistance increased significantly (p< 0.05) with a decrease in the temperature of the landrace site of origin, mainly in spring (UrS positively correlated with annual temperature, April to June and September mean temperature, April and May maximum temperature, March to June and September to November minimum temperature (Table S9).
Table 9
Discussion
The Spanish core collection of tetraploid wheat (Triticum turgidum L.) assessed in this research represents the genetic variability of more than 550 traditional varieties coming from all the agroecological zones of durum wheat cultivation in the country. Therefore, the variability found for leaf rust resistance may reflect, to a certain extent, the adaptive value of such genetic diversity to the environmental conditions prevailing in each region. Previous studies have shown that this collection possesses a high genetic variability for important adaptive traits related to the origin site [24,32].
Some of the Spanish landraces showed hypersensitive resistance to the three isolates evaluated at seedling stage. Different resistance expressions to the three isolates were detected. Eighteen accessions expressed resistance to the three isolates simultaneously (63%, 20% and 14% of the domesticated emmer, rivet and durum wheat accessions, respectively). All the susceptible accessions to the common wheat leaf rust isolate (PG14) were also susceptible to both durum wheat leaf rust isolates (especially in rivet wheat), whereas the accessions resistant to one of the durum wheat isolates (CDJ13 or JDJ15) were also resistant to the common wheat isolate. Other accessions, despite showing resistance to the common wheat leaf rust isolate, were susceptible to the two durum wheat leaf rust isolates. These results seemed to indicate that resistance genes to one of the durum wheat isolates provided resistance to the common wheat isolate, but some accessions (mostly of subsp. durum) could have other different resistance genes that are effective to common wheat leaf rust isolate. These different reactions to common and durum wheat isolates agreed with the results reported by [5]. These authors found an average similarity in virulence of 60% between different common wheat leaf rust isolates and a worldwide collection of leaf rust from durum wheat.
The studied accessions displayed higher resistance to the common wheat isolate than to the durum wheat isolates at the seedling stage in agreement with the finding in a durum wheat worldwide collection [43]. The common wheat isolate analysed PG14 is one of the races that inflict yield losses in common wheat crop in northern Spain. Our results confirm that common wheat isolates are not adapted to infect durum wheat, and therefore most durum genotypes are resistant to isolates from common wheat. According to other studies, many durum lines and cultivars possesses Lr72 that protect them against most of common wheat isolates [5]. In fact, Lr72 gene was present in 85% of the CIMMYT durum wheat lines by 2001 [18]. However, in the case of landraces it seems that this gene is less frequent or absent, so other genes, especially present in the domesticated emmer and durum wheats could confer cross resistance [5].
The two durum wheat isolates developed in Spain in different time periods. The CDJ13 represents the new races detected in 2013, virulent for the main leaf rust genes Lr14a and Lr72 [44]. In contrast, JDJ15, collected in one of the most important endemic zones of rust in Spain, although collected in 2015, represented the older races, avirulent to Lr14a gene. A strong relationship between the two durum wheat leaf rust isolates was detected based on the significant correlations obtained between them for the three infection parameters (infection type, disease severity and leaf necrosis). Accordingly, the 90% and 75% of the accessions expressing resistance to CDJ13 and JDJ15, respectively, were resistant to both isolates, which is in agreement with durum wheat isolates from Europe had an average similarity in virulence of 90% [5,45]. This result indicated that these resistant genotypes have R-genes that are effective to both durum wheat isolates. That gene might be one of the few known genes present in durum wheat (i.e., Lr23, Lr61, Lr Cam ) [46] or can be a new gene, not described so far. These genotypes were more frequent in accessions of domesticated emmer wheat and less common in those of durum. Seven accessions (one domesticated emmer and six durum wheat) showed resistance to JDJ15, but not to CDJ13, which could be due to the presence of an allele of the gen Lr14 [47]. Only one accession (of rivet wheat) was resistant to CDJ13 and susceptible to JDJ15. Despite the new races that appeared in 2013 were more virulent, it seems that sources of resistance effective to those races can be found in the Spanish landraces.
The rust resistance values assessed for the two isolates from durum wheat at the seedling stage were significantly related to those obtained in adult plants in field plots, suggesting that these two isolates were similar to those present in the field. It is remarkable that field evaluation took place in Jerez de la Frontera, near the Lower Guadalquivir Valley, a Spanish region prone to wheat rust disease [4]. The higher correlation of the field data with the results of JDJ15 (collected at Jerez) respect to those with CDJ13 was in agreement with this latter developed in Spain in the following years (2013), and probably was absent in the field when the evaluation was carried out in 2008. At this time, races more similar to JDJ15 were probably present in the field. The significant correlation, however, obtained between resistance values to CDJ13 and severity values in the field confirmed the high similarity between both durum wheat isolates. It thus seems reasonable to use the field results to confirm the associations found with seedling resistance.
The evaluation of partial rust resistance is of relevance because a key characteristic of genes expressing a partial resistance is that they confer resistance to all known races of P. triticina (horizontal resistance). However, these (minor) genes do not provide complete resistance that is manifested by many R-genes conferring hypersensitive resistance with no uredinia produced. Nonetheless, these genes provide durable resistance since virulent forms of P. triticina have not yet been detected [48,49]. In a study relating leaf rust resistance of European common wheat landraces and their origin, it was found that regions with high or intermediate severity of leaf rust led to landraces with a higher level of partial resistance. [21] In the present study, partial resistance to leaf rust was correlated with late heading and low temperatures of the origin site, mainly in spring. Although only three domesticated emmer wheat accessions were included in the analyses, their presence could influence the obtained results. However, it is remarkable that thermal variables were the only ecogeographic data correlated with the partial resistance, despite the significant differences observed in the hydric variables between the collection sites of domesticated emmer wheat and the other two subspecies in the accessions analysed. Separate analyses for each subspecies revealed that a higher resistance level was related with late heading and prostrate plant habit in rivet wheat. These agronomic characteristics are adaptive traits to cold areas. It thus seems that lateness and colder collection zones could be a criterion to select Spanish landraces of durum wheat with higher probability of possessing partial resistance to leaf rust. Partial resistance is a quantitative trait, largely affected by diverse factors of the environment. Low temperature increases the difference in leaf rust severity between a susceptible and a partially resistant genotype [50]. Thus, in a colder, although slightly, environment during the wheat growing season, it is more likely that the farmers of the past more easily identified a partially resistant landrace.
The analysis of each subspecies to the leaf rust response variability indicated that domesticated emmer wheat presented a greater resistance in all the evaluations (at seedling and adult plant stages, and for partial resistance). These results confirmed the interest of this subspecies as a donor of genes for resistance to pathogens [51,52]. In the case of leaf rust, domesticated emmer wheat is the origin of the Lr14a gene and of a novel adult-plant resistance genes, Lrac104 [53,54]. Spanish domesticated emmer landraces can be of particular interest as genetic analyses have indicated that they are quite distinct from other domesticated emmers [55]. In general, the subsp. durum had a better resistance response to the common wheat isolates than the rivet wheat, in spite of the high genetic similarity between both subspecies [32,55].
A clear association was detected between seed colour and seedling resistance or rust severity in adult plants. In both cases, the resistant genotypes had a higher frequency of red seeds. This relationship is consistent with the fact that domesticated emmer wheat had red seeds and was the most resistant subspecies to both isolates. These observations indicate a genetic linkage between resistance and seed colour genes in the landraces analysed. In a previous study, [56] a significant association between seed colour and some DArTs markers (rPt-0996 and wPt-0665) located on chromosome 3BL in a set of Spanish landraces was found. The former marker was also associated to endosperm yellow pigment. In the present study, a significant positive correlation between IT values for JDJ15 and yellow pigment (data from [55]) was detected for the subsp. durum (r = 0.54, p = 0.0001), which seems to confirm that some resistant genes could be located on chromosome 3BL. Different Lr genes have been described on this chromosome arm such as the newly described gene Lr77, derived from the hard red winter wheat cultivar Santa Fe [57], and the Lr79 from the Portuguese durum wheat landrace AUS26582 [58].
The few relations found between seedling resistance and late heading could be due to late genotypes that progress better in rainy zones in Spain with moderate temperatures, where rust attacks are more frequent. This result agreed with the greater resistance and late heading of domesticated emmer wheat (181 days vs. 177 and 173 for rivet and durum wheat, respectively). Other authors have also detected a positive influence of days to heading on the resistance to stem rust in common wheat [59].
The underlying hypothesis for the associations between ecogeographic conditions and resistance to pathogens was that certain types of environments would favour the emergence of disease resistance within in situ populations of landraces. The associations between resistance traits and ecogeographic variables of the collection site can help to identify those environments that are likely to impose selection pressure for the emergence of resistance genes. In the present study, the analyses of 75 ecogeographical variables indicated that there are significant differences between the origin sites of the resistant and susceptible accessions of durum and rivet wheat. These differences were mainly related to thermal variables of the site for CDJ13 (isothermally), and to both thermal and hydric variables for JDJ15. For the latter isolate, resistant genotypes most likely came from zones with a uniform temperature, avoiding thermal stresses in the hottest season, and with higher rainfall from October to February. The importance of these bioclimatic differences between the origin sites of resistant and susceptible groups were also shown with the random forest classification and in adult plant in the field evaluations. Furthermore, the mean values of these ecogeographic variables in the resistant/susceptible groups were similar at both growth stages (Tables S4 and S7). These results were again consistent with the higher resistance of domesticated emmer wheat since the origin sites of this subspecies (mainly northern Spain) had the highest mean temperature uniformity, and October and November precipitation (Table S10). The east of the country (Valencia Community and Balearic Islands) included more resistant durum and rivet wheat accessions to the durum wheat isolates at seedling stage than the other zones. It is known that this Spanish region is a favourable zone for leaf rust occurrence [60]. Although this result could not be confirmed at the adult stage in the field trial, this agroecological zone is characterised by having uniform temperatures and higher October precipitation, in agreement with other studies that also found significantly higher numbers of durum wheats resistant to stem rust than expected in the Spanish eastern coast [59].
Table 10
As a general rule, leaf rust uredospores needs a temperature around 20 • C and a high humidity for at least three hours (usually before dawn and resulted in dew deposition on the leaves) to start an asexual cycle [3]. Our results revealed a higher influence of temperature uniformity than hydric variables for both durum wheat isolates, which confirmed that pathogens respond more to the diurnal temperature variation than to other ecogeographic variables [30]. Some authors have also found stronger associations between rust severity and thermal variables than with hydric variables in common wheat [61,62], whereas other studies pointed out the importance of the rainfall within the growing season [63]. In our study, the rainfall in autumn and winter (from October to February) was positively associated with resistance to JDJ15. These months correspond to the growth period from the first leaves to the end of tillering. After the dry summer period, October and November are the first months the precipitation increases ( Figure S2). Winter conditions also affect the survival of the primary inoculum of leaf rust [62,64]. The humidity is also relevant at the end of winter (February), when the temperature increases ( Figure S2), resulting in a higher rust severity in the origin site. Other studies in common wheat have reported that leaf rust is associated with warm, rainy growing seasons [65,66]. In our study, the variables related to temperature uniformity and maximum values were more relevant for both isolates. This could be due to the other studies referred to common wheat, grown in colder zones where low temperatures can reduce leaf rust development, whereas high temperatures can be a more relevant limiting factor in durum wheat growing zones. The lack of relation between resistance to the common wheat leaf rust isolate and the origin site of the landraces is expected as common wheat isolates are not specialized to infect durum wheat [7], and the pathogen pressure of this kind of isolates was probably low in the zone of origin for the development of an adaptive resistance.
The relations between resistance and some ecogeographic variables of the collection site at both seedling and adult stages indicated that landraces from some areas could provide genotypes more resistant to some durum wheat isolates from Spain. Several studies [67][68][69] have shown that genetic variation for resistance to pests and diseases can be detected in germplasm originating from locations with an environmental profile similar to the collection sites of a reference set of accessions with known resistance. In the present study, two predictive models for leaf rust resistance were elaborated for the durum wheat isolates based on the seedling test scores of the core collection and the bioclimatic variables as the predictors. The goal of the germplasm testing program is to postulate which genotypes have seedling rust resistance genes and to determine if these genotypes are resistant in the field. In durum wheat, almost all resistance genes are effective through all plant stages (seedling resistance genes), with some rare exceptions such as the landrace Gaza that carries one adult plant and one seedling resistance gene [18]. Thus, both models were used to predict the resistance reaction of adult plants since this is the one disease response relevant for breeding. Although the development and validation of the models were based in leaf rust scores recorded at two different growth stages, the results indicated that both models had a high accuracy and agreement between predictions and disease resistance at adult stage. The correct classification score with the models was higher than 89% and sensitivity values were of 80%. Other studies have shown that prediction models based on ecogeographic variables is an efficient approach for the identification of rust resistant accessions [28][29][30][31]. These studies based on adult plant scores from different environments reported sensitivity values between 65 and 74% [28,29,31] and correct classification about 77% [29,31]. The better performance of the models developed in the present study could be due to the environmental conditions of the field trial are specific of the isolate attacks (the same province for CDJ13 and the same locality for JDJ15). It has been reported that different screening conditions between the sets for develop and evaluate the model can introduce variation in the trait scores that would be interpreted as noise by the classification algorithm. [29] Thus, the environmental conditions in which the evaluation data for the development of the model are obtained may influence the predictive power of the models. In the present study, this influence could be low since the data used to build the model were obtained under controlled conditions in the greenhouse.
Journal of Economic Dynamics and Control, 2005
Preparative Biochemistry & Biotechnology, 2005
Research Policy, 2011
Neuroscience Letters, 2012
Journal of Information Privacy and Security, 2013
RISALAH KEBIJAKAN PERTANIAN DAN LINGKUNGAN: Rumusan Kajian Strategis Bidang Pertanian dan Lingkungan, 2018
Clinical Epidemiology and Global Health
Journal of Materials Chemistry C, 2017
Bulletin of the British Ornithologists’ Club, 2023