Introduction

Chickpea (Cicer arietinum L.) is one of the most important food legumes cultivated worldwide. It has two main types, Desi and Kabuli, which are grown in over 50 countries, with 90% of its production and consumption in developing countries (Joshi et al., 2001). The desi chickpeas are small and brown coloured while kabuli chickpeas are large and cream/white coloured. These chickpeas are cultivated on 13,111,816.6 ha of lands producing 63,669,396 million tons and 969.5 kg ha−1 worldwide from 2013 to 2017 (FAOSTAT, 2019). The major producers of this crop are Australia, Canada, Ethiopia, India, Iran, Mexico, Myanmar, Pakistan, Spain and Turkey (Muhammad et al., 2014). Ethiopia is the 3rd largest producer of this crop after India (65%) and Myanmar (14%), comprising approximately 4% of the global chickpea production (FAOSTAT, 2019). Among the African countries, Ethiopia is the largest chickpea producer, contributing 40.53% of the continent’s total chickpea production (FAOSTAT, 2018). The crop is the third most important legume crop in Ethiopia after faba bean and common bean in terms of its production, with an average national yield of 2137 kg ha−1 (FAOSTAT, 2018). It is mainly grown in the Amhara (50.4%), Oromia (43.4%), SNNP (4%) and Tigray (2.2%) regions in Ethiopia (CSA, 2017/18).

Although chickpea is widely grown in Ethiopia, its productivity is still very low. The mean chickpea yield in Ethiopia in farmers’ fields is below 2000 kg ha−1, which is far below its potential yield of > 5000 kg ha−1 (Zewdie, 2018). This low productivity is mainly due to several biotic and abiotic production constraints. Consequently chickpea production fluctuates annually with an erratic harvest determined by biotic and the abiotic stresses (Aslam et al., 2018). Among the abiotic constraints, drought at different growth stages of the crop cycle is a major yield constraining factor in arid and semiarid regions of major chickpea producing countries, such as India, Pakistan, Turkey, Iran and Ethiopia (Singh et al., 2008). Among the biotic constraints, Ascochyta blight caused by Ascochyta rabiei (teleomorph: Didymella rabiei) is the most disastrous fungal disease of chickpea. Ascochyta blight has been reported in almost all chickpea growing regions across the world and is deemed to be the most devastating biotic factor, resulting in significant loss of yield and degradation of seed quality (Megersa et al., 2017).

The disease affects every component of the chickpea plant's shoot, including the leaves, stems, and pods, resulting in lesions and breaking of the shoot (Pande et al., 2005). Ascochyta blight symptoms include wilting leaf tips, leaf lesions, stem lesions causing stem breaking, and seed infection on pods. These symptoms appear on all aerial portions of the plant (Sally, 2005), and consist of necrotic lesions with a distinct border and multiple pycnidia forming in the centre (Pande et al., 2005). Because the disease is polycyclic (has numerous infection cycles during the season), infection can happen at any time throughout the growing season if the conditions are right for it (20—25 °C). The disease epidemics may cause up to 100% grain yield/quality losses (Wazir, 2019), however in Ethiopia, up to 41.3% yield losses have been reported due to Ascochyta blight epidemics (Amin and Melkamu, 2014), and it is therefore considered as one of the most important foliar diseases of chickpea (Asrat, 2015).

In Ethiopia, the disease was first observed at Kulumsa in 1969, and later at Debrezeit (currently Bishoftu) in 1976–77 in a small plot of chickpea (Geletu, 1994). However, in the following year, occurrences were also reported from the chickpea fields at Bishoftu, Negele, Arsi, and Mekele, where it is assumed that the disease was transported with the seeds from Bishoftu (Geletu, 1994). Currently, the disease has been reported from all the chickpea growing areas of the country. Although there is no empirical evidence determining whether the disease was introduced from abroad or was indigenous to the country, it is assumed that it was introduced with imported seeds of the cultivars Punjab7, C 217/3, C 410 (Geletu, 1994). Currently, the area suitable for chickpea production in Ethiopia is partially limited by Ascochyta blight along with lack of drought tolerant varieties suitable for short growing seasons (Megersa et al., 2017). However, except for limited survey activities in some chickpea growing areas, the distribution and importance of Ascochyta blight and its association with cultivation practices, geographic variables and environmental factors has not been analysed and determined in the major growing areas of central Ethiopia. Thus, as chickpea Ascochyta blight has become a recurrent problem in major chickpea growing areas of Ethiopia, a survey is useful to gain insights into the distribution and relative importance of the disease, and to understand how to better manage the disease. Understanding the relationship between disease severity and various cropping systems and cultivation techniques will assist in pinpointing the most crucial factors and concentrate efforts on creating sustainable management strategies (Fininsa & Yuen, 2001). Despite this, Ethiopia lacks information on the prevalence of the disease, the significance and consequences of various agronomic techniques, environmental conditions, and other biophysical factors on Ascochyta blight of chickpea. Therefore, the purpose of this study was to ascertain the distribution, incidence, and severity, and to determine the connection between the disease's intensity and the farming techniques and agro-ecological parameters in central Ethiopia.

Materials and methods

Description of the survey area

Chickpea Ascochyta blight survey was conducted in five main chickpea agro-ecological zones during 2020 and 2021 main cropping seasons from early September to late December in central Ethiopia. The altitude of the survey areas ranged from 1609 to 3206 meters above sea level (m.a.s.l.). Weather data for the surveyed areas were obtained from national meteorological stations and presented in Table 1 and Fig. 1. The areas mainly differed in altitude, temperature, relative humidity, planting time and rainfall (Table 2). The overall soil type of the study area is verity soil and light silty-loam. A total of 366 chickpea fields were inspected at seedling to maturity growth stages, and growers were interviewed to collect the history of the field’s data. The spatial and temporal distribution of Ascochyta blight, chickpea agronomic practices and other pests including major weed species in each zones were inspected. The selection of the zones were based on their chickpea production and productivity status.

Table 1 Monthly mean weather data of the surveyed areas in Ethiopia during the chickpea growing seasons (August to January) of 2020 and 2021
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Fig. 1
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Map of Ethiopia and the Zones surveyed for Ascochyta blight (Didymella rabiei) during 2020 and 2021 main cropping seasons in Oromia and Amhara Regional States, central Ethiopia

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Table 2 Time of different planting chickpea data of the surveyed areas in Ethiopia during the chickpea growing seasons of 2020 and 2021
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Survey, sampling, and data collection

Beginning from one to two months after planting, assessment for Ascochyta blight prevalence, incidence and severity were conducted in the selected survey areas of central Ethiopia. A total of 366 fields were inspected for Ascochyta blight intensity in which 186 fields were surveyed in 2020 cropping season, and remaining 180 fields surveyed in 2021 cropping season (Table 3). The surveys and interviews were conducted following main and feeder roads on pre-planned routes in the main chickpea producing regions. Assessment for Ascochyta blight was carried out along the two diagonals (in an “X” pattern) at five to nine points depending on the field size, within a 0.5 m × 0.5 m (0.25 m2) quadrat. All of the plants in each quadrat were considered sampling units. Visual identification of the diseases and other pests was carried out in all visited fields. In each field, chickpea plants within the quadrats were counted and recorded as either diseased/infected or healthy/not-infected with Ascochyta blight. During the survey, altitude (m.a.s.l), cropping pattern (row or broadcast planting), weed management, the presence or absence of other pests, crop growth stage, and plant density (number of plants per m2) were recorded for each sampled field. Growers were asked information on the cropping system used, chickpea cultivar and variety, and cultivation practices (crop rotations grown for the last two cropping seasons). Furthermore, the time of planting of the crop was obtained from each surveyed fields through interview (Table 2).

Table 3 Categorization of variables used in analysis of the survey data of Ascochyta blight of chickpea in central Ethiopia, during the 2020 and 2021 crop seasons (n = 366)
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Disease prevalence was determined as the ratio of the number of fields where Ascochyta blight was present to the total number of fields assessed. Disease incidence was determined as the proportion of diseased plants per quadrat. Disease severity was recorded from 13 randomly selected chickpea plants, by observing symptoms of the target disease, and using a hierarchical sampling strategy was adopted (McDonald and Martinez, 1990). The level of disease severity for each field was determined using a visual 1–9 disease rating scale (Jan & Wiese, 1991; Chen & Muehlbauer 2003; Chen et al., 2004; Sharma et al., 2005 and Pande et al., 2011), where 1 = no lesions visible on plant; 2 = minute lesions prominent on the apical stems; 3 = lesions up to 5‒10 mm in size and slight drooping of apical stems; 4 = lesions obvious on all plant parts and clear drooping of apical stems; 5 = lesions common on leaves, small lesions on stem but causing little damage; 6 = lesions as in 5, defoliation, broken, dry branches common, some plants killed; 7 = lesions very common on leaves and stem, resulting in the death of some branches; 8 = symptoms as in 7 but up to 50% of the plants killed and 9 = lesions on all parts of the plant (resulting in the death). Disease severity scores were converted into a severity index (SI) for the analysis (Wheeler, 1969; Chiarappa, 1981; Fininsa, 2003).

$$\mathrm{Disease}\;\mathrm{prevalence}\;\left(\%\right)=\frac{\mathrm{Number}\;\mathrm{of}\;\mathrm{fields}\;\mathrm{affected}\;\mathrm{by}\;\mathrm{Ascochyta}\;\mathrm{blight}}{\mathrm{Total}\;\mathrm{number}\;\mathrm{of}\;\mathrm{fields}\;\mathrm{assessed}}\times100$$
$$\mathrm{Diseases}\;\mathrm{incidence}=\frac{\mathrm{Number}\;\mathrm{of}\;\mathrm{plant}\;\mathrm{diseased}\;\mathrm{per}\;\mathrm{quadrat}}{\mathrm{Total}\;\mathrm{no}\;\mathrm{of}\;\mathrm{plant}\;\mathrm{observed}}\times100$$
$$\mathrm{Percentage}\;\mathrm{of}\;\mathrm{severity}\;\mathrm{index}\;(\mathrm{PSI})=\frac{\mathrm{sum}\;\mathrm{of}\;\mathrm{numerical}\;\mathrm{ratings}}{\mathrm{Number}\;\mathrm{plants}\;\mathrm{scored}\;X\;\mathrm{maximum}\;\mathrm{score}\;\mathrm{on}\;\mathrm{the}\;\mathrm{scale}}\times\;100$$

Agronomical practices such as crop rotation, crop cultivar, sources of seed, the cropping pattern, altitude, planting date, weeding conditions and weed density, plant growth and number of plant stands were assessed to determine their relationship with the disease intensity and distribution. Finally, representative diseased plant parts were collected for laboratory diagnosis and confirmation of the pathogen.

Data analysis

Descriptive statistical analysis was performed on all data collected from each field to summarize the field survey data. In addition, data analysis was conducted to determine the distribution and association of Ascochyta blight intensity in relation to the independent variables (Table 4). Where a significant difference for disease incidence existed, the mean disease difference was separated using the T-test at P < 0.0001. In the second analysis, the independent variables and variables class were categorized based on the frequency of fields (Table 4). Contingency tables of the disease severity and independent variables were built to represent the bivariate distribution of the fields according to data classifications.

Table 4 Lists and information of chickpea varieties grown by farmers, and Ascochyta blight intensity during 2020 and 2021 cropping seasons in central Ethiopia
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The associations of Ascochyta blight intensity with cropping systems and cultivation practices were analysed using a logistic regression model (Fininsa & Yuen, 2001; Yuen, 2006), using the SAS procedure of GENMOD (SAS, 2003). The logistic regression model allows evaluation of the importance of multiple independent variables that have an effect on the response variable (Fininsa & Yuen, 2001). The response variable (disease incidence or severity) was categorized into zone groups of binomial qualitative data as described by Woldeab et al. (2007) and Yuen (2006). Thus, class boundaries were chosen based on an overall mean, such as ≤ 30 and > 30 for incidence and ≤ 35 and > 35 for severity (SI) data, yielding a binary dependent variable. Thus, the response variable was the chance that Ascochyta blight incidence exceeds 30% and severity exceeds 35% in a given chickpea field (Table 5). The importance of the independent variables was examined in two ways (Belete et al., 2013; Woldeab et al., 2007). First, the association of all the independent variables with Ascochyta blight intensity was tested in a single-variable model. This consisted of testing the deviance reduction attributed to a variable when it was first entered into the model. Second, the association of an independent variable with Ascochyta blight incidence or SI was evaluated when entered last into the model with all other independent variables. Lastly, selected independent variables that have a significant association with Ascochyta blight incidence or SI when entered first and last into a model were added to a reduced multiple variable model. The deviance table was constructed for the final reduced multiple variable as described by Yuen et al. (1996). Deviance reduction was calculated for variables as it was added to the reduced model and the likelihood ratio test was used to evaluate the significance of the variables and was examined against Chi-square value (McCullagh & Nelder, 1989). The odds ratio that was obtained by exponentiation of the parameter estimate was used for comparing variable classes based on the reference point.

Table 5 Mean distribution of Ascochyta blight of chickpea intensity for different independent variables in central Ethiopia, during 2020–2021 cropping seasons
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Results

Chickpea surveyed fields

The survey was conducted in major chickpea producing areas, with altitudes ranging from 1609 m.a.s.l. in the East Shewa zone to 3206 m.a.s.l. in the North Shewa zone (Table 1). The highest mean plant density (54.4 m2) was recorded in the East Shewa zone. Only 47.54% of the surveyed fields were found to be used for crop rotations with other crops. With respect to the planting pattern, 97% of the surveyed fields were planted by broadcast planting, while the rest were row planting (Table 4). Assessment of Ascochyta blight over two successive years showed that the disease intensity decreased from 2020 to 2021 (Table 4). Weed management practices were carried out in different fields, with weeds found in different densities and frequencies, with high weed densities observed in both the East Shewa and North Shewa zones. The chickpea fields were at different growth stages at the time of the survey, at seedling (6.01%), vegetative (34.8%), flowering (19.67%), full podding (15.85%), and maturity (23%). The highest Ascochyta blight incidence (78.43%) was recorded in East Shewa zone in 2020 and in 2021 (62.06%).

Ascochyta blight prevalence and intensity

Different levels of Ascochyta blight intensity were recorded in the different survey areas (Fig. 1). The disease was more prevalent in Arsi, East and North Shewa zones than in West and South West Shewa zones in both 2020 and 2021 cropping seasons (Fig. 2). The survey result revealed that Ascochyta blight was the most prevalent chickpea disease in over 76.5% of the fields. The disease incidence varied up to 78.43% among the sampled fields, with over 63% of the fields having an incidence of more than 33% (Table 5 and 3). The Ascochyta blight severity index (SI) was generally high (mean = 60.3%) and varied significantly between zones and over the growing seasons (Table 5). The maximum mean SI value of the disease was 60.3%, while the minimum was 29.5%. Mean SI was high in Arsi zone located in moderately low altitude (SI = 60.3%), while West Shewa zone located in high altitude had the lowest mean (SI = 32.1%) (Table 5).

Fig. 2
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Graph showing prevalence in bars and intensity in curves during 2020 and 2021 main cropping season in five surveyed zones of central Ethiopia

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Furthermore, West and South West Shewa zones had lower disease incidence than the East (78.43%) and North Shewa (73.97%) zones (Table 5). Over the two seasons, SI was highest at low altitudes (Table 5). The zones that had higher Ascochyta blight prevalence and intensity had moderate levels of rainfall and higher temperatures relative to the other zones (Table 1). In Ethiopia, it has been reported that chickpea is cultivated at altitudes ranging from 1400 to 2300 m.a.s.l. (Bekele et al., 2007). However, during the survey, chickpea fields were also found at 2300 m.a.s.l that appear to have been used as major chickpea production areas for a long time. Higher prevalence (80.81%) and intensity (78.43%) of Ascochyta blight disease were observed at an altitude of ≤ 2129 m.a.s.l than > 2129 (69.05% and 73.33%, respectively) m.a.s.l (Table 5), indicating that low-altitude chickpea growing environments of Ethiopia were more favourable for Ascochyta blight disease than higher altitude environments. These results indicated that the incidence and prevalence of Ascochyta blight of chickpea increased as the altitude range decreased.

When the crop canopy is dense and vegetative, and temperatures are suitable for disease growth, the disease primarily grows in September and October. Incidence decreased from 81.7% in 2020 to 73.6% in 2021. The study also revealed that Ascochyta blight severity was higher in lower altitude locations compared to higher altitude areas, and that the interplay between altitude and season rather than each factor alone had an impact on the disease's development (Table 4). These points again reinforce the need to undertake successive cropping season studies of Ascochyta blight across different altitudinal ranges in central Ethiopia. Regarding weather variables, the study revealed which weather conditions were made conducive for development and increment incidence of Ascochyta blight, specifically that East Shewa and Arsi zones, which had higher Ascochyta blight prevalence, were characterized by moderate rainfall amounts and higher temperatures, showing that these weather conditions were favourable for Ascochyta blight development (Table 1).

Association of Ascochyta blight intensity with biophysical factors

The association of all independent variables with Ascochyta blight intensity is presented in Table 6. A multiple regression model indicated that the independent variables significantly affected both the disease incidence and severity index. The independent variables, such as region (χ2 = 406.68, 1df), cropping season (χ2 = 1900.06, 1df), zone (χ2 = 746.41, 4df), altitude (χ2 = 24.37, 1df), seed source (χ2 = 99.73, 4df), variety (χ2 = 204.28, 10df), planting pattern (χ2 = 146.59, 1df), plant density (χ2 = 303.37, 1df), weed density (χ2 = 1446.74, 2df), growth stage (χ2 = 53.32, 4df), crop rotation (χ2 = 330.20, 14df), planting time (χ2 = 83.48, 3df), fusarium wilt infection (χ2 = 26.69, 1df), dry root rot infection (χ2 = 4.54, 1df), pod borer infestation (χ2 = 91.71, 1df), aphid Spp. infection, and rust infection (χ2 = 14.34, 1df) were significantly (P ≤ 0.0001) associated with Ascochyta incidence and severity index when entered into the logistic regression model as single variables. Likewise, except for the region, when entered last into the regression model all variables had a significant association with both the incidence and severity index. However, variety, black root rot infection, and virus infection were not significantly associated with incidence or severity when entered either first or last into the model. This indicates they lost their importance when entered into the reduced variable model.

Table 6 Independent variables used in logistic regression model of Ascochyta blight intensity and their likelihood ratio test (LRT) for variables entered first and last into a model a
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Among the independent variables, the dry root rot infection (χ2 = 4.54 and P 0.0332, 1df) on disease incidence did not show an increase/decrease, while aphid spp. infection showed a slow increase in contrast to the chickpea growth stage and planting time to incidence, which showed a strong increase in the reduced model (χ2 = 53.32, χ2 = 102.85) (Table 6). This indicates that the growth stage was the most important variable in its association with incidence and SI when entered first and last into the model. Except for region, cultivar, virus, black root rot, and rust infections, the independent variables were tested in a reduced multiple variable model. The deviation analysis of these variables in a reduced multiple variable model showed the importance of their association with incidence. The output from this reduced model indicated the importance of the variables and variable classes. Higher Ascochyta blight disease incidence (> 30%) was linked to altitudes of < 2129 m.s.a.l, cropping season (2020), seed source (market, owner, farmers seed producers association), planting pattern of broadcasting, plant population/m2 of > 39, growth stage of seedling and flowering, and weed density of high and medium, mono-cropping practices, early and late of planting time, fusarium wilt, dry root rot, pod borer, aphid spp., and rust in the north shewa, Arsi, and East shewa zones.

The independent variables were examined in a reduced multiple variable model except for region, cultivar type, virus, black root rot, and rust (Table 7). The relevance of these variables association with incidence was revealed by deviation analysis of these variables in a simplified multiple variable model. Table 7 displays again the parameters estimates, standard error, and odds ratio. The chance of disease occurrence in North Shewa zone of Amhara region was higher than in the East Shewa zone of Oromia region, and had a positive association with all chickpea varieties except Dhera. Except for Dhera, chickpea variety with low Ascochyta blight disease severity index (> 35%) had a risk of being associated with Ascochyta blight. The parameter estimates and standard error and odds ratio are presented in Table 8.

Table 7 Analysis of deviance, natural logarithms of odd ratio and standard error of Ascochyta blight incidence, and likelihood ratio test (LRT) on independent variables
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Table 8 Analysis of deviance, natural logarithms of odd ratio and standard error of Ascochyta blight severity, and likelihood ratio test (LRT) on independent variables
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Discussion

Ascochyta blight was found to be widespread in the major chickpea growing areas during the survey periods, indicating that it is the major limiting factor of chickpea productivity. About 76.41% prevalence of this disease was recorded during both cropping seasons of the survey. High mean Ascochyta blight prevalence may be due to the cropping practices used such as use of poor quality farmer-saved seed, lack of crop rotation due to land scarcity, and poor management practices by farmers in the study areas, together with environmental conditions conducive for disease development. Assessment of Ascochyta blight incidence over two consecutive cropping years showed that the disease incidence was lower in 2021 (Table 4). Factors related to Ascochyta blight epidemics were identified using logistic regression analysis (Table 5). It is helpful to understand how disease epidemiology is affected by various factors when developing sustainable management strategies. According to the current research, altitude, weed density, pod borer, aphid spp., cultivar, variety, and year (crop season) of assessment, and region all have a substantial impact on the ascochyta blight disease epidemics and are highly likely to be linked to the severity of the disease.

The mean disease incidence and severity index varied between variable classes of seed source and planting time. The results indicated that the disease is widespread across the different agro-ecological areas, affecting the quantity and quality of chickpea, which causes low crop productivity. Megersa et al. (2017) also reported that in almost all chickpea cultivating regions across the country the most devastating biotic factor is Ascochyta blight, which results in significant loss of yield and degradation of seed quality. During the study, it was observed that chickpeas form a lush canopy creating a humid microclimate for disease development, however with weed infestations the canopy closure was suppressed. The same has been recorded earlier, with studies concluding that early canopy closure reduced the impact of weeds on subsequent crop growth (Martin et al., 2001 and Mohammadi et al., 2005). However, most farmers do not understand how to time weed management in their chickpea fields because they also use the weeds as animal feed, and so tolerate high weed densities within their chickpea crop.

The highest mean Ascochyta blight prevalence may be due to the farming practices adopted by smallholder farmers in the study areas; findings of this study confirmed the reports of Njingulula et al. (2014) who emphasized use of poor quality farmer-saved seed, lack of crop rotation due to land scarcity, and poor management practices exacerbated by conducive environment conditions for disease development. In 2020, there was a conducive environment for the disease development due to high relative humidity, temperature, and rainfall compared to the cropping season 2021 across surveyed region (NMSA, 2020, 2021). Logistic regression analysis was used to identify factors associated with Ascochyta blight epidemics (Table 6).

Designing sustainable management methods requires an understanding of disease epidemiology, which is influenced by a variety of factors. In the current study, significant factors that influence the Ascochyta blight disease epidemic and have a high likelihood of association with Ascochyta blight intensity were identified as region, cropping system, cropping season, altitude, weed density, pod borer, aphid spp., variety, and year (crop season) of assessment. There were mean incidence and severity variation between variable classes of seed source and planting time. Disease severity was variable and ranged from minimum to maximum (1–9) in both cropping seasons. Even in a single field, there was variable severity, and fields exhibited 1–5 Ascochyta blight severity. Thus, the study revealed that the disease is widespread across the different agro-ecological study areas affecting the quality and quantity which leads to hindering chickpea production. Khan et al. (2018) also confirms and reported that Ascochyta blight present in almost all chickpea cultivating regions across the world and is deemed to be most devastating biotic factor causing significant loss of yield and degradation of seed quality.

Several epidemics of Ascochyta blight resulting in complete yield loss have been reported by different researchers across the world including Ethiopia (Islam et al., 2017). Knights and Siddique (2002) also confirmed Ascochyta blight as the most important chickpea yield limiting factor that potentially affects 95% yield of the crop. This study showed that the economic impact of the disease in the two cropping seasons depends on the variety, weather conditions, and influence of management practices. In addition, different production practices including weed management, nutrient management in terms of crop rotation and cropping systems, along with agro-ecology and cropping seasons were influencing Ascochyta blight occurrence, Ascochyta blight development, and the level of crop damage. Similar observations were made by Tekeoglu and co-workers in 2000 (Tekeoglu et al., 2000), who stated that Ascochyta blight is an important constraint on chickpea production worldwide. Chickpea production regions, cultivar, virus, black root rot, and rust had no effect on diseases severity, however aphid spp. and dry root rot had a small effect on disease severity.

One of the findings of this study contradicts a previous report, which stated that cultivars with compound leaves (kabuli type) were less prone to Ascochyta blight disease than unifoliate lines (Ahmed et al., 2006). In the current study, plant density ranged between ≤ 39 and > 39 plants m2 in over season, and it was observed that high plant densities were consistently associated with high levels of Ascochyta blight (Table 5). Throughout the survey it was observed that there were a higher number of pod borer-infected plants and aphid spp. with Ascochyta blight in densely populated fields than in sparsely populated fields. Thus, the study revealed that Ascochyta blight severity was slightly reduced in less dense fields. This may be due to reason that close proximity of host plants increases the number of plants available to intercept inoculum and reduces the chance of inoculum being lost to the soil. Secondary spread of Didymella rabiei occurs via rain-splash dispersal of conidia, which is associated with steep disease gradients (Burdon and Chilvers, 1982; Mundt et al., 1999). Similarly, other study also reported that in densely populated farm fields, the disease incidence was higher due to plant-to-plant spread of the foliar diseases as a result of the wind or rain splashes (Harrison, 1980).

Regarding the cropping pattern, mean disease incidence in row planted fields was higher (47.9%) than that in broadcasted fields (39.2%), but conversely mean severity was higher (58.0%) in broadcasted fields than row planted fields (41.5%) (Table 5). Ascochyta blight infects chickpea at all growth stages and on all plant parts. Pande et al. (2005) suggested that Ascochyta blight attacks the plants at any growth stage in diseased fields, and is an important foliar disease of chickpea worldwide that causes up to 100% grain yield and quality losses. Reddy and Singh (1984) confirmed that moderate Ascochyta blight epidemics are most prominent during the flowering and podding growth stages. Therefore, information on chickpea resistance to blight at different growth stages may be important in order to select the best stages for inoculating plants to screen for Ascochyta blight resistance. In addition, the study revealed that Ascochyta blight severity varies between locations, altitude, weed management practices, plant density, seed source, variety, planting pattern, growth stage, planting time, and crop rotation.

Scheuermann et al. (2012) also confirmed that disease occurrence and severity may vary by cropping season, location, and even within field depending on environmental conditions and crop management practices. With regarding to crop rotation, higher Ascochyta blight incidence and SI were observed in chickpea fields not rotated with non-host crops (39.30 and 40.51%) than fields rotated with non-host crops (28.69 and 32.79%). Mohammdi (2019) confirmed that sowing of disease free seed, rotation of crops in such a manner that non host crop follow the host crops, elimination of crop residues, and deep sowing of crop have been found most effective to minimize disease incidence. Furthermore, Rubiales et al. (2018) stated that deep ploughing to eradicate the disease debris/ infected plant residues, rotation of non-host crops, destruction of residues of previous crop, and sowing of the resistant genotypes have been found most effective to control the disease.

Accordingly, high mean disease incidence was recorded from fields sown in early season. During the study, each growing chickpea area was practiced at different planting times based on soil character and agroecology. Thus the late August planting time for East Shewa, Arsi, and North Shewa zones was set very early as the starting time for West and South West Shewa zone. Even if they are under the same zone different time of planting was obtained (Table 2). This indicates that a middle sowing date reduced the disease risk in chickpea fields than early planting. According to Ejeta and Hussein's findings, Ascochyta blight was less prevalent and had more of an impact on the intermediate planting date than the early and late sowing dates (2015). Agro-ecological and environmental characteristics unique to each area, agronomic and management approaches, a variety of meteorological conditions, and variations in sowing dates in various fields could all contribute to the reported disparity in disease intensity.

In addition, the study showed that Ascochyta blight severity was highest at lower altitudes compared to the higher altitude areas. Furthermore, the interaction of altitude and season had an effect on the disease development, rather than each alone (Table 3).

Differences in weather conditions between crop seasons likely contributed to the disease intensity, and similar studies reported that Ascochyta blight prevalence and severity depend on the occurrence of favourable weather (Chongo & Gossen, 2001; Chongo et al., 2002, 2004). Nene (1982) stated that low humidity is a more critical factor in limiting the disease incidence than the temperature. Similarly, in this study, both incidence and SI of Ascochyta blight was found to decrease as relative humidity reduced. However, Trapero-Casas in 1982 reported that disease severity increases with increases in relative humidity. Similarly, the occurrence, spread, and severity of disease in nature are primarily controlled by different environmental factors. Favourable environmental conditions have large effects on the initiation and spread of the disease infections. Furthermore, the growth and development of Ascochyta blight fruiting bodies occurs rapidly at 20 °C (Trapero-Casas and Kaiser, 1992). In the study areas, wherever the disease was observed, it was uniformly distributed. The long cool and moist weather spells are considered to be the most conducive for conidia oozing, and rain splashes disperse them to surrounding plant populations (Armstrong et al., 2001). The disease becomes epidemic in cool and humid environments (Sharma & Ghosh, 2016). Subsequent wetness, strong winds and rain splashes accelerate the dispersal of conidia from infected plant parts to healthy populations (Pande et al., 2005).

Conclusions

The results of this study indicated that Ascochyta blight is widely distributed, and a major disease in chickpea growing areas of central Ethiopia. It is a particularly devastating disease in East Shewa zone of Oromia and North Shewa zone of Amhara, where relatively high temperatures along with wet weather conditions prevail during the main cropping season. In addition, the study identified that disease incidence varies between zones, and with the date of planting, chickpea variety, weed management practices, and environmental factors. Cropping practices, such as the use of poor quality seed, lack of crop rotation, and poor management practices may have contributed to the high occurrence and severity of the disease. In addition, Ascochyta blight severity is influenced by locations and varied between cropping seasons. The results obtained from this study indicated the importance of research on planting time, crop rotation, planting pattern, using different varieties, and other related cultural practices to develop Ascochyta blight management options, both in the surveyed areas and also elsewhere with similar agroecological conditions.

The findings of the present study recognized that Ascochyta blight incidence and severity varies between zones, seasons, growth stages, cultivar type, agronomic practices, and climatic factors. Thus, the findings of the study showed that Ascochyta blight is a major constraint of chickpea production, implying the need for proper intervention to improve available chickpea varieties through appropriate weed management, use of fungicide, healthy seed in the study areas (known seed source), and other related cultivation practices. Likewise, proper integrated management strategies should be applied to reduce Ascochyta blight impact on chickpea production and productivity particularly for the chickpea growing belt of central Ethiopia.