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Epidemiology and forecasting of Alternaria blight of oilseed Brassica in India - A case study
Abstract
Experiments were laid out at Bharatpur, Mohanpur, Berhampur, Pantnagar, Dholi, Kangra, Faizabad and New Delhi with oilseed Brassica juncea cultivars 'Varuna' and an important cultivar in the locality sown on 10 dates at weekly intervals. First appearance of Alternaria blight disease (Alternaria brassicae) on leaves of mustard occurred between 42 and 139 days after sowing (d. a. s.), 44-72, 42-61 69-83, 45-60, 67-84 d. a. s. having higher frequencies in 1999-2000, 2000-01, 2001-02, 2002-03 and 2003-04, respectively, being highest in respective years at 45, 46, 75, 45, 76 d. a. s. The disease first appeared on pods between 67 and 142 d. a. s., being highest at 99 d. a. s. Severity of Alternaria blight disease on leaves was positively correlated to a maximum daily temperature of 18-27°C, minimum daily temperature of 8-12°C, daily mean temperature > 10°C, > 92 % morning relative humidity (r. h.), > 40 % afternoon r. h. and mean r. h. of > 70 % in the preceding week. Disease severity on pods was favoured by a maximum daily temperature of 20-30°C, daily mean temperature of > 14°C, morning r. h. of > 90 %, daily mean r. h. of > 70 %, > 9 h of sunshine and > 10 h of leaf wetness. Temperature and r. h. conditions favourable to disease development noted in the field matched with laboratory findings. Regional and cultivar-specific models could predict the crop age at which Alternaria blight first appeared on leaves and pods, the highest blight severity on leaves and pods and the crop age when blight severity was highest on leaves and pods at least one week ahead of first appearance of the disease on the crop. This will allow farmers to make timely and effective fungicidal sprays. Only models with reasonable prediction accuracy when tested with an independent data set are reported.
... The tender leaves of these cultivars serve as vegetable, while the seeds as a source of lubricating and cooking oil. The residue left after oil extraction being rich in protein (Durrani and Khalil, 1990;Chattopadhyay et al., 2005) [6,3] can be used as livestock feed. It produces 9 k cal energy from 1gm of oil per unit in comparison with other diets (carbohydrate and Protein). ...
... The tender leaves of these cultivars serve as vegetable, while the seeds as a source of lubricating and cooking oil. The residue left after oil extraction being rich in protein (Durrani and Khalil, 1990;Chattopadhyay et al., 2005) [6,3] can be used as livestock feed. It produces 9 k cal energy from 1gm of oil per unit in comparison with other diets (carbohydrate and Protein). ...
... In traditional medicines, it is used to relieve the pain associated with arthritis, muscle sprains and strains. (Chattopadhyay et al., 2005) [3] . It is second largest indigenous oilseed crop, In India, rapeseed-mustard is grown over in diverse agro-largest indigenous oilseed crop which contributing 32 per cent of total oilseed production in India (Gupta et al., 2017) [9] . ...
... Sacc., is responsible for 10-70 % losses. Severity of Alternaria blight on oilseed Brassicas differ among seasons and regions as also between individual crops within a region in India (Chattopadhyay et al., 2005). This may also be due to the existence of variability among geographically similar isolates of A. brassicae. ...
... Reasons for tolerance in some germplasm accessions against Alternaria blight at some location(s) that did not hold good for other sites, were not known. Further, variation in severity of Alternaria blight of Indian mustard is a regular phenomenon, which hitherto was attributed to variation in weather and host plant conditions (Chattopadhyay et al., 2005). In order to generate resistant material in oilseed Brassicas against Alternaria blight, knowledge about pathogenecity of A. brassicae isolates from different geographical regions of India is important, which too was so long unavailable in earlier reports. ...
... Sacc., is responsible for 10-70 % losses. Severity of Alternaria blight on oilseed Brassicas differ among seasons and regions as also between individual crops within a region in India (Chattopadhyay et al., 2005). This may also be due to the existence of variability among geographically similar isolates of A. brassicae. ...
... Reasons for tolerance in some germplasm accessions against Alternaria blight at some location(s) that did not hold good for other sites, were not known. Further, variation in severity of Alternaria blight of Indian mustard is a regular phenomenon, which hitherto was attributed to variation in weather and host plant conditions (Chattopadhyay et al., 2005). In order to generate resistant material in oilseed Brassicas against Alternaria blight, knowledge about pathogenecity of A. brassicae isolates from different geographical regions of India is important, which too was so long unavailable in earlier reports. ...
... Under field conditions, the disease becomes epidemic when the temperature is around 12 o C, RH > 70% (mostly between 60-80%), wind velocity from 2.7-3.4 km/h and winter rains are found as the most congenial. The severity of white rust on leaves was favored by RH > 40% afternoon (minimum), > 97% morning (maximum) and 16-24 o C maximum daily temperature [20]. ...
India is one of the world’s largest producers of oilseed crops. Among the oilseed crops of India, Indian mustard (Brassica juncia L.) has shared the maximum account of the edible oilseed production, which is also considered the backbone of the Indian agriculture economy. Recently the production of Indian mustard is decline due to adverse climatic conditions. Hence, the changes in climatic conditions also increase the pest attacks on the crops. The present investigation documented the correlation of weather factors on the prevalence and severity of the Alternaria blight and White rust on Indian mustard. The experiment was conducted with eight dates of sowing viz. October (1, 10, 20, and 30), November (10, 20, and 30), and December (10) of the mustard crop (var. Varuna) in the field during the Rabi season at 10 days intervals. The results revealed that the maximum severity and apparent infection rate (r) of Alternaria blight and white rust were recorded on the sixth (November, 20) and eighth (December, 10) date of sowing, respectively. Among dates of sowing, the maximum seed yield was recorded at first date of sowing (20.41 q/ha) followed by second (19.99 q/ha) and third (19.16 q/ha). Overall, our findings suggested that early-sown crops escaped the disease outbreak and give higher yields compared to late-sown crops.
... Parada et al (2007) reported that destruxin B is not a host-selective toxin and does not induce accessibility of host plants Alternaria brassicae. Resistance to Alternaria brassicae is found to be layered and multicomponent with sensitivity to host-specific toxin destruxin B, quantitative and qualitative elicitation of phytoalexins, hypersensitive reaction, and Ca sequestration determining the fate of hostpathogen interaction (Chattopadhyay et al 2005). The resistant Brassica varieties also produce some metabolites, namely, sesquiterpenes, deoxyuvidin B, albrassitriol, isoalbrassitriol, and brassicadiol (Saharan et al 2015). ...
Alternaria leaf blight caused by Alternaria brassicae L. is one of the most widespread and destructive disease of oilseed brassicas species in all the continents. The average yield loss of 30 to 60% was recorded in rapeseed due
to this disease in Nepal. Fourteen rapeseed (Brassica campestris) genotypes were received from Oilseed Research Program, Nawalpur, Sarlahi evaluated for disease reaction against alternaria leaf blight at Hill Crops Research Program, Kabre, Dolakha during winter seasons of two consecutive years 2020 and 2021. The genotypes were planted in Randomized Complete Block Design in three replicated conditions having three replications. The unit plot size was 3m x 2m with 30 cm row to row distance with continues plant to plant spacing was maintained. The experiment was planted at first week of October in both the years. Chemical fertilizer was applied @ 60:40:20 N:P2O5:K2O kg/ha and 20 kg/ha Sulphur. Seed rate was 6 kg/ha. Other
agronomic practices were followed as per protocol provided. Disease assessment was done following 0-5 scale. The grain yield and other yield parameters were recorded. All evaluated genotypes differed significantly (p<0.05) against alternaria leaf blight disease severity and grain yield. Among the tested genotypes, Bal Tori,
ICT2002-11 and ICT2002-10 reacted moderately resistance with higher grain yield. This result can be utilized and incorporated in the breeding program for the improvement and development of alternaria leaf blight tolerant/ resistant rapeseed variety with high yielding for the mid hill conditions of Nepal.
... A wide gap exists between the potential and the realized yield at the farmers's field, which is largely due to number of abiotic and biotic stresses to which the rapeseed-mustard crop is, exposed (Jha et al., 2013). Diseases and insect pests are the main limiting factors, which decrease Research Article cent (Chattopadhyay et al., 2005). Under Punjab conditions, the alternaria blight disease caused by Alternaria brassicae is an important disease. ...
... The disease intensity also decreased when K (40kg/ha) along with recommended dose of fertilizers was applied. Chattopadhyay et al. (2005) analyzed the data for Alternaria blight progression and development from eight locations using cv 'Varuna' sown on 10 dates at weekly intervals. The results revealed that first appearance of disease on leaves occurred between 42 and 139 days after sowing (DAS). ...
The brassicaceae family, to which the genus Brassica belongs, contains many important plants yielding high quality edible and industrial oils, some common vegetables and weeds. Rapeseed comes from several species belonging to the genus Brassica that include B. napus L., B. rapa L. (= B. campestris L.) and B. juncea (L.) Czern. & Coss. which are known as rape, turnip rape and leaf mustard, respectively? India is one of the leading oilseeds producing abstraCt an epidemic is the progress of disease in time and space. each epidemic has a structure whose temporal dynamics, and spatial patterns are jointly determined by the pathosystem characteristics, and environmental conditions. One of the important objectives in epidemiology is to understand such spatio-temporal dynamics via mathematical and statistical modelling. Knowledge of epidemiology and forecasting provides the basic information to develop efficient and workable plant disease control methods. The various weather variables such as temperature (T), relative humidity (RH), rainfall, wind velocity and direction, leaf wetness duration, and solar radiation influence different parameters of infection process, and disease development. Interaction between these weather variables (independent variables) and disease development (dependent variables) pave the way for the development of the prediction models. The average productivity of rapeseed-mustard, an important oil seed crop in India, is quite low due to infection by several diseases such as Alternaria blight (Alternaria brassicae) white rust (Albugo candida), downy mildew (Hyaloperonospora parasitica), powdery mildew (Erysiphe cruciferarum), and white or Sclerotinia stem rot (Sclerotinia sclerotiorum). These diseases are being managed through chemical fungicides, but the efficiency of control measures depends upon the interaction between pathogen and host, which is influenced by environmental factors. Prediction models developed for the management of important diseases of rapeseed-mustard are discussed here. Development of alternaria blight is favoured by tmax of 20-25 O C, tmin of 15 O C, rhmor > 90% and rheve > 50%. For white rust, tave of >15 O C and rh >65% with intermittent rains proved most effective for disease development. Similarly, for downy mildew, a T range of 15-20 O C with high rh was considered optimal for its progress. Leaf wetness duration of 4-6 h at 20 O C and 6-8 h at 15 O C is essential to initiate the downy mildew infection. stag-head due to mixed infection of downy mildew and white rust is favoured by a t 20 O C with high RH. A reduced period of sunshine (2-6 h/d) with rainfall up to 161 mm during flowering favours the stag-head formation. Powdery mildew development is favoured by t range of 16-28 O C, mean rh <60% and dry weather especially during February-March. the white stem rot or sclerotinia rot disease progression is favoured by high RH (>80 %), Tmax up to 25 O C and tmin of 5-12 O C. Often prediction models developed at one location may not fit at other locations. It indicates that data need to be generated for a longer period and the model be tested at multilocations. For greater efficiency, the disease-forecasting models must be developed by taking into account the crop variety, the prevalence of a particular pathotype and the microclimatic factors.
... Since weather has overriding influence on disease development, monitoring the weather conditions under different dates of sowing is an important consideration in disease forewarning models. This may enable the prediction of disease occurrence and to advise growers to do timely fungicidal sprays for an efficient crop management (Chattopadhyay et al., 2005). The incidence of Alternaria blight in rapeseed-mustard fields is influenced by air temperature, relative humidity, soil conditions at the time of sowing, splashing rain, wind velocity, leaf wetness, and inoculum density available in the soil (Meena et al., 2011). ...
... Most of the earlier workers have utilized regression models (both linear and non linear) for pests and diseases forewarning Chattopadhyay et al., 2005aChattopadhyay et al., & 2005bDesai et al., 2004 andDhar et al., 2007). These techniques are being successfully applied across an extraordinary range of problem domains, in areas as diverse as finance, medicine, engineering, geology, physics, biology and agriculture. ...
Artificial Neural Networks model have been used in plant pathology to study dynamics, modeling and forecasting of several disease in recent years. Artificial neural networks are parallel computing systems made up of a large number of simple, highly interconnected processing elements called nodes or neurons that process information by their dynamic-state response to the external signals and can handle imprecise information. It provides a flexible way to connect disease outcome with environmental and other determinant variables. ANN can automatically approximate any nonlinear mathematical function. This aspect of neural networks is particularly useful when the relationship between the variables is not known or is complex and hence it is difficult to handle statistically. Due to the nature of linear relationship in the parameters, regression models may not provide accurate predictions in some complex situations such as non linear data and extreme values data. As regression models need to fulfill the regression assumptions and multiple co-linearity between independent and dependent variables, it causes regression models to be inefficient. The ANN model has non-linear pattern recognition capability which is valuable for modeling and forecasting complex non-linear problems in practice. Neural networks are similar to regression models, in that both develop coefficients that model patterns by evaluation of the relationship between independent and dependent variables. However, neural networks don't require hypothetical information for modeling, unlike parametric statistical models. In general, neural networks consist of three or more groups of elements that represent sets of equations used by the model. These recently developed Artificial Neural Network (ANNs) techniques are interesting and have become the focus of much attention, largely because of their wide range of applicability and the ease with which they can treat complicated problems even if the data are imprecise and noisy. As disease can occur over the conditions provided by the host plants as well as when weather conditions are favourable. Therefore, there is a need to develop effective forewarning model, which can provide advance information for outbreak of the disease. In this paper an attempt is made to reveal the potential use of ANN in disease prediction.
... Weather is an important determinant in the population dynamics of the pests. Most of the earlier workers studied the weather and pest-relationship utilizing regression models (both linear and nonlinear) for insect-pest forewarning (Desai et al. 2004, Chattopadhyay et al. 2005a, 2005b, Dhar et al. 2007, Agrawal and Mehta 2007, Laxmi and Kumar 2011a, 2011band Kumar et al. 2013. These studies restricts to evaluate short term relationship between weather and pest. ...
Changes in climatic variables may affect phenological phases of crops and affect plant growth and development, these changes also lead to emergence of new pests and diseases. Therefore, there is need to relate the trends of climatic parameters with rice productivity vis-á-vis the pest dynamics in the crop at different sites apart from projecting a future scenario for the crop in the country. For this long-term seasonal, monthly and weekly trends in climatic data, viz. temperature (maximum and minimum), relative humidity (morning and afternoon), rainfall and bright sunshine hours on seasonal (kharif or rainy season, rabi or post-rainy season and summer), monthly (January to December) and weekly (1-52 standard meteorological week or SMW) time scales for the period 1970–2010 at 14 different agroclimatic centers situated in rice growing regions of India were investigated. Mann–Kendall and Sen’s slope estimator, non-parametric test were used for studying the magnitute as well as statistical significance of trend in climatic data. Trend analyses of the climatic variables in rice growing regions of different locations (Palampur, Chiplima, Jagdalpur, Kaul, Cuttack, Kanpur, Hyderabad, Bengaluru, Samastipur, Pantnagar, Parbhani, Varanasi, Pune and Coimbatore) in India were studied. Positive trend for maximum temperature [for kharif season varied from 0.006°C/yr (Pune) to 0.045°C/yr (Chiplima)] were observed at five locations, negative trends [maximum for Jagdalpur (0.047°C/yr) and minimum for Bengaluru (0.011°C / yr)] were observed at eight locations while one location showed no change in maximum temperature. Minimum temperature showed increasing trend at most of the locations in kharif seasons. Relative humidity in the morning and afternoon also showed increasing trend at most of the locations in kharif. Increase in rainfall for kharif season varied from 8.990 mm/yr (Chiplima) to 0.008 mm/yr (Parbhani); the decrease was highest for Jagdalpur (5.329 mm/yr) followed by Coimbatore (4.485 mm/yr) and least for Varanasi (0.213 mm/yr). Positive and negative trends for total rainfall were observed at seven locations each. In kharif season (23-39 SMW), weekly maximum temperature showed a rising trend except at Cuttack, Kaul, Bengaluru, Pantnagar, Parbhani and Coimbatore while minimum temperature showed the increasing trend except at Palampur, Kanpur and Parbhani. Rainfall pattern showed a falling trend except at Cuttack, Hyderabad, Chiplima, Pune and Coimbatore. Monthly analysis of maximum temperature indicates that the trends are increasing in months of February, March, April, July, August and November while the trends are decreasing in months of January, May, June, September, October and December at most of the locations. Mimimum temperature showed an increasing trend in all months except January. Rainfall showed negative trends in monthly total rainfall during June-September. In June, seven locations showed negative trends which varied from 0.246 mm/yr (Kanpur) to 3.703 mm/yr (Jagdalpur); in July, 10 locations indicated negative trends that varied from 0.231 mm/yr (Samastipur) to 2.144 mm/yr (Chiplima); in August and September eight locations had negative trends. Coimbatore showed negative trends in monthly rainfall from May to December, the decrease was highest for November (4.854 mm/yr) and least in June (0.246 mm/yr). Based on these trends in climatic variables, monthly projected mean and seasonal change till 2050 were also obtained. The changes in climatic variable can be utilised for identification of the hotspot zones of important pest of rice based on the physiological aspect of pest. These changes may lead to possible rise in blast disease of rice at Kaul, Hyderabad and Pune. There looks a possible trend in reduction of the yellow stem borer insect-pest on rice crop in Central and Peninsular India with rise in the Northern latitudes of the country. There is need to relate the trends of climatic parameters with rice productivity vis-á-vis the pest dynamics in the crop at different sites apart from projecting a future scenario for the crop in the country. © 2018 Indian Council of Agricultural Research. All rights reserved.
... Besides abiotic factors, more than 30 diseases are known to occur in rapeseed-mustard with varying degree of severity among seasons and regions within India [3,4]. The crop is ravaged by several diseases viz., Alternaria blight, white rust and Sclerotinia stem rot which are serious threats to sustain higher production and yield stability [2,3]. ...
... Alternaria blight severity on rapeseed & mustard differs among seasons and regions and also between individual crops within a region in India (Kumar et al. 2010).Since weather has overriding influence on disease development therefore, monitoring the weather conditions under different dates of sowing is an important consideration in disease forecasting models. Which may enable prediction of its occurrence so as to allow growers to take timely fungicidal sprays for an efficient crop management (Chattopadhyay et al., 2005). The present investigation is planned with the aim of finding the correlation between Alternaria blight disease and weather factors and to develop a disease forewarning model. ...
Investigation on major insect pests in tomato was carried out at Agronomy Farm, B. A. College of Agriculture, Anand Agricultural University, Anand during rabi seasons of 2012-13 and 2013-14. Whitefly population was noticed from 39th standard meteorological week (SMW) with maximum population in 45th SMW (2.72 whiteflies/ 3 compound leaves). Aphid population was noticed from 42nd SMW with highest peak in 52nd SMW (0.98). Maximum larval population of leaf miner was observed in 48th SMW with number of larva 0.86 per 3 compound leaves. The activity of Helicoverpa armigera commenced from 39th SMW with larval population in the range of 0.12 to 1.86 per 3 twigs. Correlation study was carried out to find out impact of abiotic factors on the activity of insect pests. Wind speed on whitefly, H. armigera, leaf miner, spider; maximum temperature on aphid and spider; evening relative humidity on whitefly, aphid, leaf miner and evaporation on aphid were key abiotic factors influencing significantly on the fluctuation of the pests. © 2017, Association of Agrometeorologists. All rights reserved.
... Weather is an important determinant in the population dynamics of the pests. Most of the earlier workers have utilized regression models (both linear and nonlinear) for insect pest disease forewarning [Desai et al. (2004); Chattopadhyay et al. (2005aChattopadhyay et al. ( , 2005b; Dhar et al. (2007); Agrawal and Mehta (2007); Kumar (2011a, 2011b); Kumar et al. (2012) and Kumar et al. (2013)]. However, they provide no insight into quantitative prediction of the yellow stem borer and leaf folder on the rice crop for different seasons. ...
Loss in yield and quality of crop produce due to pest infestation could be reduced considerably if the pest occurrence is known in advance and timely remedial measures are taken. Weather plays an important role in pest development. Therefore, weather based models can be an effective scientific tool for forewarning pests in advance. In this study, weather based forewarning models have been developed for yellow stem borer [Scirpophaga incertulas(Wa\ker)] and leaf folder [Cnaphalocrocis medinalis(Guenee)] of rice for different locations, viz., Aduthurai (Tamil Nadu), Chinsurah (West Bengal), Karjat (Maharashtra), Mandya (Karnataka), Ludhiana (Punjab) and Raipur (Chhattisgarh). The pest data comprised of population of yellow stem borer and leaf folder moths caught in light trap per week for different locations. Weather data relating to maximum and minimum temperature (°C), morning and evening relative humidity (%) and rainfall (mm) in respect of the locations were obtained from the meteorological observatories of the locations per se. Data of pest and weather on weekly basis in respect of Kharif and Rabi seasons of 11 years (2000-2010) for all locations, and of 16 years (1995-2010) for Mandya (KA) were used for developing the forewarning models. Weather of six lag weeks from week of forecast were used for development of weather indices. These weather indices were used as independent variables in model building against the pest population as dependent variables. Stepwise regression models for predicting the yellow stem borer population for peak periods of occurrence during Kharif [Aduthurai (TN), Karjat (MH) & Raipur (CG)] and Rabi [Chinsurah (WB) & Mandya (KA)] were developed with R² > 0.9. Prediction of leaf folder for different weeks of Kharif for Aduthurai (TN) (32-35 SMW) and Ludhiana (PB) (32-36 SMW) and of Rabi for Aduthurai (TN) (44-47 SMW) gave R² between 0.6 and 0.8, respectively indicating better leaf folder prediction for Rabi over Kharif season at Aduthurai (TN). Validation of the models for subsequent years (2011) has been done for all cases. These developed models were converted into web-based forewarning system using 3-tier architecture. Net Beans 8.0.1 IDE (Integrated Development Environment), MS SQL Server, Java Server Pages (JSP) technologies have been used for the development of the web enabled forecasting of the two rice pests.
... Three leaves from each genotype were inoculated individually with the help of atomizer with a conidial suspension of 5 9 10 4 conidia/ml. Control leaves were sprayed only with DW. Chattopadhyay et al. (2005) positively correlated the severity of Alternaria blight disease on leaves to a maximum daily temperature of 18-27°C, minimum daily temperature of 8-12°C, daily mean temperature >10°C, >92% morning relative humidity (r. h.), >40% afternoon r. ...
... Field screening though provides the information about the actual performance of genotype, it often varies in the diverse natural environment, and thus lacks authenticity. The occurrence of a disease depends on congenial environmental conditions like relative humidity, temperature, sunshine hours and pathogen inocula (Chattopadhyay et al., 2005). Conidium of Alternaria starts germination in free water and penetrates host tissues through stomata at 25 o C temperature with minimum leaf surface wetness period of 6-16 h for initiation of the infection (Verma and Saharan, 1994). ...
Alternaria blight (AB) caused by Alternaria brassicae (Berk.) Sacc. is a devastating disease of oilseed Brassicas all over the world,and responsible for significant seed yield losses up to 47%. No reliable,resistant germplasm is available to develop AB resistant cultivars. Various screening techniques have been reported so far,but cotyledonary leaf method is not yet reported. Three methods were tested using one susceptible cultivar (Varuna): inoculation of seed,inoculation of cotyledons,and inoculation of both seed and cotyledons. Fungal conidia were inoculated directly onto the seedlings with 1.5×10⁵,2.5×10⁵,4×10⁵ and 5×10⁵ conidia ml⁻¹ concentrations for standardization. Percentage AB severity increased with the increase in conidial concentration,therefore the highest concentration was used for final screening. Among the three screening methods,inoculation of both seed,and cotyledon method was found highly effective where mean AB severity on cotyledon was 84.6% in comparison to 49.3% in the inoculation of seed and 62.5% in the inoculation of cotyledon methods. The technique was validated by screening susceptible and putative tolerant genotypes. The severity of AB was 54% of susceptible cultivar and 16.4%-21.2% of tolerant genotypes. The conidia number per microscopic field was 21.5 in putative tolerant and 43.5 in susceptible genotypes. Thus,in vitro screening of AB using inoculation of both seed and cotyledon method was found most effective and could be used for rapid screening in early stages of plant growth. A new 0-7 rating scale was also devised to observe the AB pathogen interaction phenotype at the cotyledonary stage of oilseed Brassica.
... There are indications that some Brassica genotypes possess a degree of resistance to powdery mildew, but most reports are from field experiments or anecdotal (Bradshaw et al. 1989;Shivpuri et al. 1997;Singh and Singh 2003;Gaetán and Madia 2004;Tonguc and Griffiths 2004;Chattopadhyay et al. 2005;Singh et al. 2010;Chattopadhyay and Kolte 2015). In France, Penaud (1999) indicated that all available B. napus cultivars were susceptible to powdery mildew. ...
Powdery mildew of brassicas, caused by Erysiphe cruciferarum, is an emerging threat to oilseed Brassica production in Australia. Resistance to powdery mildew was assessed in 112 current and historic Australian Brassica napus canola cultivars and five cultivars of B. juncea mustard cultivars under controlled environmental conditions. Only 18% of leaf area was infested by the end of the test on the most resistant cultivars, compared with means of up to 70% for the most susceptible cultivars as well as severe stem and pod infection. For B. napus, cultivars with the greatest potential for reducing the impact of powdery mildew in the field were Trooper, Bravo TT, Summit, Tumby, Narendra and Hyola 650TT, all ranked in the 10% of cultivars with the lowest leaf infestation (Area Under The Disease Progress Curve (AUDPC) <537) and with <10% of stem area infested. For B. juncea, the level of leaf infestation was lowest for Sahara CL and Xceed X121 CL (AUDPC 303 and 380 respectively), but the high levels of stem infestation (42% and 28% respectively) in these cultivars may reduce their usefulness in the field. The most resistant cultivars identified can be immediately deployed into regions where powdery mildew is prevalent, providing the canola industry with an immediate and effective option for management of this increasingly troublesome disease.
... Besides abiotic factors, more than 30 diseases are known to occur in rapeseed-mustard with varying degree of severity among seasons and regions within India [3,4]. The crop is ravaged by several diseases viz., Alternaria blight, white rust and Sclerotinia stem rot which are serious threats to sustain higher production and yield stability [2,3]. ...
Abstract Indian mustard, Brassica juncea (Linn.) Czernj
and Cosson is ravaged by several diseases viz., Alternaria
blight, Sclerotinia stem rot, white rust and nutrient deficiency
causing substantial yield loss. A field experiment
was conducted on the integrated management of major
diseases in Indian mustard through different combinations
of balanced fertilization, cultural practices and restricted
use of fungicides (as seed treatment and foliar spray) to
observe their role in augmenting the seed yield and its
attributes in calcareous soil at the Indian Agricultural
Research Institute, Regional Station, Pusa, Bihar (India)
during 2012–2013 and 2013–2014. Seed treatment with
propiconazole plus two foliar sprays of propiconazole at 70
and 80 days after sowing showed lowest per cent disease
index of Alternaria leaf blight (2.40), pod blight (8.61),
white rust (1.39), Sclerotinia twigs infection (1.90) and
Sclerotinia stem rot (8.76) in comparison to other treatments
and control during both the years. However, integrated
treatments i.e. seed treatment with propiconazole
(0.1 %) ? balanced fertilization ? removal of four lower
leaves at 60 days after sowing ? one foliar spray of
propiconazole (0.1 %) at 70 days after sowing resulted in
second lowest severity and incidence of major diseases.
This treatment produced significantly highest yield
(2339 kg/ha) and its attributes in comparison to control
(1050 kg/ha) and remaining treatments. Thus, inclusion ofmicro and secondary nutrients, cultural practices and
restricted fungicidal spray in combination had a beneficial
effect on yield enhancement of rapeseed–mustard with
substantial reduction in all the major diseases.
... The Alternaria blight is major disease of rapeseed and mustard. Chattopadhyay et al. ( 2005 ) studied the time of appearance of A. brassicae on the host cultivar ( B. juncea var. varuna) and the role of environmental factors on disease severity of Alternaria blight disease. ...
Alternaria spp. of ascomycete fungi are known as major plant pathogens causing 20–80 % agricultural losses in field crops, horticultural crops, plantation crops, forest plants and also post harvest storage. Conventional methods of phyto-pathogenic Alternaria spp. identification is only based on their symptomatology of diseases, morphological, physiological and biochemical studies. However, identification based on formae specials, strains, or ecotypes within a species of Alternaria has limitations for accurate diagnostics, identification and detection. The species identification of these pathogenic groups of fungi is somewhat difficult because of their special growth conditions and morphological differences. The advancement of immunological assays and serological methods has shown more sensitivity and accuracy compared with earlier isolation techniques. Enzyme analysis, metabolic profiling and gel electrophoretic mobility of these pathogen proteins found to be useful for the detection of some strains and species. There are different rapid molecular diagnostics available for the detection of pathogenic Alternaria sp. including a range of pathogenic fungi like Fusarium and Macrophomina sp. Various methods based on detection and analysis of the internal transcribed spacer (ITS)-5.8S ribosomal DNA (rDNA) region are designated to be a powerful tool for precise and rapid laboratory diagnosis. However, the developments of polymerase chain reaction (PCR) variants which employ nucleic acid-based diagnostic techniques including reverse transcription (RT)-PCR, nested-PCR, multiplex-PCR, RT-PCR, RAPD and nucleic acid hybridizations are more rapid, sensitive, specific and reliable. Various commercial kits for in situ detections are available with reproducible results in a short time. Recently, with development of DNA micro-array technology and Fourier transform infrared spectroscopy (FTIR) has revolutionized the fungal phytopathogens identification and has become possible to detect different isolates of Alternaria. Nevertheless, the genomics and proteomics studies through bioinformatics tools are also supplementing with promising results. Though, the wide ranges of diagnostics techniques are available for detection, identification and quantification of Alternaria spp., the polyphasic approaches is best and more reliable than only molecular and serological methods. The sensitivity, specificity, rapidity, cost-effectiveness and their on-site suitability determines choice of the diagnostic methods. In management practices, integrated disease management (IDM) including physical, cultural, chemical and biological methods is the best strategy for Alternaria diseases. Judicious use of resistant germplasm and multi target fungicides provides sustainable advantage for management of diseases. However, development of bioinoculents and disease forecasting module will enable better strategies for eco-friendly disease management. Diversified group of fungi that have been reported as opportunistic pathogens, it is imperative that their specific identification be made correctly by an experienced microbiologist or mycologist. The species detection specific to Alternaria and development of diagnostics using molecular tools and technique is an upcoming challenge for the researchers and sustainable plant disease management.
... In addition to its immediate predictive value, a weather-driven model provides a natural candidate for investigating the impact of climate change on cardamom. The potential of disease prediction model to minimize loss has been recognized; however, most of the earlier workers on disease prediction have utilized regression models (both linear and nonlinear) to develop forewarning models of different pests [11][12][13][14] . Several other works have also explored application of forecast models for plant diseases like onion botrytis 15 and Alternaria solani on tomato 16 . ...
Small cardamom is an economically important spice crop. However, cardamom is susceptible to several diseases that significantly reduce yield. Proactive prevention of these diseases based on advance warning can enhance the efficiency of disease control and reduce environmental load of pesticides. Many of these diseases are governed by weather variables (for example, through control of fungal growth). This work presents a disease (capsule rot of cardamom) forecast model based on a set of meteorological variables. While no single weather variable provides successful simulation, an optimal combination of weather variables provides sufficient skill for advance warning of the disease.
... A weather-based model can be an effective scientific tool for forewarning diseases in advance so that protection measures can be implemented before the actual onset of the damage. Most of the earlier workers have utilised regression models (both linear and non linear) for pests / diseases forewarning ; Chattopadhyay et al. (2005aChattopadhyay et al. ( & 2005b; Desai et al. (2004) and Dhar et al. (2007)]. Recently Artificial Neural Network (ANNs) techniques have become the focus of much attention, largely because of their wide range of applicability and the (663) ease with which they can treat complicated problems even if the data are imprecise and noisy. ...
... Among the biotic stresses, Alternaria blight caused by Alternaria brassicae (Berk.) Sacc. is one of the most common and destructive diseases of Indian mustard causing up to 47% yield loss (Chattopadhyay 2008). The disease has also been reported from all the continents of the world with no proven transferable source of resistance against the same reported till date in any of the hosts. ...
Variation in morphology and cultural characteristics among 13 representative Indian geographical isolates from 219 collections of Alternaria brassicae, the causal agent of Alternaria blight of rapeseed-mustard, was studied. All the isolates showed high level of variability in vitro in respect of conidia length, width, beak length and number of septa. Conidia of Nazirhat isolate (SS 04) were smallest in size with lowest number of septa. Substantial variation was found in mycelial growth, sporulation among these isolates in different nutrient media and artificial environmental condition, viz temperature, relative humidity, light, hydrogen ion concentration. Different temperature ranges (25–30 o C; 15–35 o C) were found optimum for different isolates for mycelial growth and sporulation, respectively. All the thirteen isolates grew best at 100% relative humidity. However, they sporulated the most at different % relative humidity (40–100%). This reflected the adaptation of the respective isolates to the ambient conditions in the different cropping areas, where the disease occurs in varied proportions in different years, which may have also induced the available cultural variability. All the isolates did not grow and sporulate abundantly on the same nutrient medium. However, on an average Asthana and Hawker's medium was good for all the cultures. Variation in optimum pH and light condition for mycelial growth, sporulation was also observed. Cluster analysis for data on cultural variability among thirteen A. brassicae isolates found a close relationship among isolates from Uttar Pradesh, Uttaranchal and Haryana but was distantly related to others.
Reliable and timely forecasts are of pivotal importance for effective planning, especially for an uncertain field like agriculture. Crop production and pest-disease severity are the two key aspects in agriculture that require forethought. The earlier a forecast is available, the better its utility for the policy planners and traders. Because of their effectiveness in broad practical applications, various prediction and forecasting methods have received a wealth of coverage in scientific journals, technical blogs, etc. However, in most of the articles, the outcomes are situation-specific and inconclusive. This chapter aims to provide a comprehensive view of various prediction techniques of crop yield and pest-disease infestation. It also highlights the underlying assumptions and data structure required for implementing these models.
The productivity of rapeseed-mustard in India is quite low as compared to the world scenario. It is mainly due to important diseases, Alternaria blight, white rust, downy mildew, powdery mildew, and white or Sclerotinia rot. Knowledge of epidemiologyand forecasting provide the basic information to developefficient and workable plant disease control models. The various weather variableslike temperature (T), relative humidity (RH), rainfall, wind velocity, and direction, leaf wetness duration, and solar radiation influence differentparameters of infection process, and disease development. Interaction between these weather variables and disease development pave the way for the development of the prediction models. Prediction models developed for the management of important diseases of rapeseed-mustard revealed that Alternaria blight is favoured by Tmax of 20–25 °C, Tmin of 15 °C, RHmor > 90% and RHeve > 50% where as white rust influencedby > 15 °C and RH > 65% with intermittent rains. Similarly, for downy mildew, Temprange of 15–20 °C with high RH was considered optimal for its progress. Leaf wetness duration of 4–6 h at 20 °C and 6–8 h at 15 °C is essential to initiate the downy mildew infection. Stag-head due to mixed infection of downy mildew and white rust is favoured by a Temp 20 °C with high RH and reduced period of sunshine (2–6 h/day) with rainfall up to 161 mm. Powdery mildew development is favoured by Temprange of 16–28 °C, mean RH < 60% and dry weather during February–March. The Sclerotinia stemrot progression is favoured by high RH (> 80%), Tmax up to 25 °C and Tmin of 5–12 °C. Often prediction models developed at one location may not fit atother locations. It indicates that data needs to be generated for a longer period and the model be tested atMultilocation. The disease-forecasting models must be developed by taking into account the crop variety, the prevalence of a particular pathotype and the microclimatic factors.
Turnip (Brassica rapa) is a herbaceous annual or biennial root crop of Brassicaceae family, produced for its edible roots and leaves. It is highly nutritive fodder crop that has a short growing season, grown in temperate climates worldwide. Turnip is attacked by many fungal pathogens, but Alternaria alternata is one most dangerous of them causing Leaf blight of turnip by producing a number of necrotic spots on leaves. Annually, it caused 40-60 % yield losses in Pakistan and all over the world. Therefore, present study was designed to control this disease. A survey was conducted for data collection regarding disease severity, incidence and mortality due to leaf blight from Faisalabad. Diseased samples were collected and pathogen were isolated and purified. The pathogenicity test was also performed for the confirmation of pathogen. For effective management of Alternaria alternata of turnip. In this research different varieties of turnip were grown in the field among these most susceptible variety of turnip (ETP 231B) was further evaluated by plant extracts against Alternaria alternate under field and lab condition. Four plant extracts Neem, Garlic, Pepper and Coriander were used as treatments with three different concentrations (10, 20 and 30 %). Amongst Neem extracts showed best results against leaf blight disease and maximum fungal growth was observed and also showed minimum disease incidence (%) followed by garlic, pepper and coriander as compared to control.
Parthenium hysterophorus L. is considered globally as one of the most troublesome weeds, which has invaded non-cropped as well as cropped lands in many tropical and sub-tropical countries including India. Biological control using the Mexican beetle (Zygogramma bicolorata Pallister) among other agents, has been considered most successful in India. In the present study, models were developed using climatic indices (minimum temperature, maximum temperature, rainfall and relative humidity) as independent variables to determine the suitable sites for the establishment of Z. bicolorata. Regression approach for model building revealed 79.6% concordance, 20.0% discordance, and 0.4% tie between predicted probabilities and observed responses whereas, decision tree using J48 algorithm classified 81.7% instances correctly which helped to frame the rules for predicting the establishment of Z. bicolorata. Based on these rules, it was concluded that a site experiencing climate with indices values of average minimum temperature 24.2–26.2 °C and rainfall 191.2–257.3 mm during July to October would be highly suitable for setting up the Z. bicolorata population in the region. These models might be useful to decide the most suitable sites for release and establishment of Z. bicolorata in India as well as in other parts of the world with similar climatic conditions.
In agricultural field, dissemination of information regarding pest population and their occurrence is very important for taking remedial measures in advance to save the crops to a great extent. The information dissemination through mobile application is adapted due to effective and efficient way to communicate to end users at proper time. In this study mobile application development and its implementation is discussed. The application is developed with push notification feature in order to disseminate the advisories about the infestation of pest and remedial measures based on the objective forewarning of pests through statistical modeling.
(Brassica napus L.) belongs Brassicaceae family is the second most important oilseed crop in Pakistan after cotton. It
contains 40-46% oil content and 22% protein. There are several factors which lowers seed yield like abiotic and biotic stresses.
Alternaria blight and white rust diseases are the major threat for reducing Brassica seed yield in Pakistan. White Rust (WR) is the
most destructive disease of brassica in tropical and subtropical areas of Pakistan caused by Albugo candida. It causes 20-90% yield
losses throughout the world. In Pakistan, it was first reported from FATA and BAJAUR Agency with 32% pod losses and 52% foliage
losses. A. candida is an obligate parasite and its survival rate is very high in plants debris and soil. It is reported from different Asian
and European countries causing different epidemics. It has wide host range of Cruciferae, Ficoidaceae, Cappaaracea, and
Cleeeomaceae white or off-white (creamy) raised pustules of pin size to various forms, and sizes leading to stag-head formation.
Three types of spores are produced and their nature of infection is variable. Oospores are seed and air borne when carried on seed,
or overwintered in soil; serve as prime source of infection in Brassica. Through extensive research different races of A. candida are
identified on different host range. Few races like AC 2, 3, 4, 5, 6, 7, 8, 9 are common in various countries and different researcher
named them accordingly. That’s why it is being placed in different families, and genera. Infection of pathogen brings different
biochemical changes in plant. These changes in host are useful to understand the biochemistry, host pathogen-interaction and to
manage the disease by avoiding symptom’s ambiguity. Screening of resistant germplasm is a prime factor and extensive research is
being conducted in this regard. Resistant cultivars are the best option to control the disease as they are eco-friendly, locally adapted
to the environment, and durable. Different genotypes of Brassica juncea, B. carinata, B. napus and B. rapa were evaluated in field
conditions against white rust for five years. Resistant sources are mentioned in this review according to the local climate of different
countries. Chemicals protect the plants by forming layer on leaves surface while some have ability to penetrate the system and help
the plant to reverse the biochemical changes induced by the pathogen. The Symptomology of a disease plays an imperative role in
the understanding of altered physiological changes and the establishment of pathogen with in host but there are many factors
which caused the symptoms uttered by pathogenic fungus like infection time, type of infection, plant age, genetic makeup of the
host plant and environmental conditions which need further research. Biochemical changes play an important role in the plant
defense and induce resistance as the proteins form complex with fungus to inhibit it. One compound regulates the level of other
one in tissues as H2O2 is produced at a very high rate in susceptible but less in moderately resistant lines. As a defensive action on
H2O2 the quantity of CAT which led to increase in POD and SOD is increased to manipulate later and so is the way of regulating it.
Catalase (CAT) prevents the accumulation of H2O2 in the cells. CAT activity increases in resistant varieties and it breaks down the
hydrogen peroxide into water and oxygen. Peroxidase (POD) plays a significant role in defense response and its activity is associated
with resistance induction in different species of plants. It is also involved in the breakdown of hydrogen peroxide. Increased activity
of peroxidase leads to the production and accumulation of hydroxyproline rich glycoprotein into the cell wall. Peroxidase is involved
in lignin polymerization. The enzyme has role in cell wall metabolism as well as in defense regulation and induction. Superoxidase
dismutase enzyme acts as a first line of defense against reactive oxygen species (ROS) and rapid induction of SOD leads to recognize
the pathogen’s avirulence factors. phenolic contents can be increased due to glycosidic esters formed by the enzymatic activity of
host or pathogen or due to migration of phenols from uninfected tissue. Our research findings support the above-mentioned facts.
Different researcher has reported different chemicals of same formulations as Meralaxyl, Mancozeb, Captaf, Swing and Atracol to
control white rust either using them as seed treatment or foliar application. These biochemical and chemicals interactions need
more exploration.
Keywords: Antioxidant enzymes, Brassica, Racial variation, Management, White rust
The field experiments were conducted at the Experimental Station of Aleksandras Stulginskis University in 2015–2017. The aim of the experiment was to evaluate the influence of sowing time on spreading of pests and diseases in spring oilseed rape crop. The first sowing occurred when soil reached physical maturity, the other sowing dates were every 5 days in 2015–2016 and every 7 days in 2017. In 2015, the sowing time did not have a significant effect on the distribution of Alternaria brassicae. Meteorological conditions strongly influenced the severity of the disease. The sowing date had a significant influence on the distribution of Verticillium dahliae: in the spring rape crop sown in May, the stems were damaged by 6.4%, less compared to the crop sown in April. In 2016–2017, the rape seedlings in the plots of the latest sowing were significantly more damaged compared with those of earlier sowing dates. In 2016, spreading of Verticillium longisporum significantly increased by 3.7 times in the crop of spring rape sown on 10 May compared to other sowing dates. In 2017, the spreading of Verticillium dahliae in spring rape crops was more influenced by a colder than usual vegetation period and an abundant rainfall than the sowing time. In 2015, the intensity of Phyllotreta spp. damage in the rape seedling period (BBCH 10-19) significantly increased by 2.7 times with the sowing date from 30 April to 20 May. The spreading of Meligethes aeneus was the least in the spring oilseed rape sown at the optimal time (30 April and 5 May). In 2016–2017, Phyllotreta spp. were more intensively spread in the crops sown in April, and rape seedlings were significantly more damaged. In 2016, Meligethes aeneus were most widely spread in the spring rape crop of the earliest sowing (4 October). A significant decrease in the number of pests was detected in the rape crops sown in May compared to that sown in April. In 2017, the highest number of Meligethes aeneus was evaluated in the rape crop sown on 2 June, significantly by 3.9 times more compared with that in the earlier sown crop and by 2.9 times in the crop sown one week later. It is believed that the other generation of Meligethes aeneus from winter rape crops went to the spring rape crops. In 2016, there was a very strong statistically significant correlation between the sum of positive temperatures for the 10-day period up to the sowing of rapeseed and the prevalence of Phyllotreta spp. in crops: r = 0.98, P ≤ 0.05, and the damage intensity of rape seedlings by Phyllotreta spp. of (BBCH 10-19): r = 0.92, P ≤ 0.05. The warmer the weather was before rape sowing, the more active Phyllotreta spp. were. In 2017, strong correlations were established between the number of Phyllotreta spp. and the intensity of crop damage by Phyllotreta spp. and the crop density 3 days after the emergence: r = –0.82, P ≤ 0.05; r = –0.89, P ≤ 0.01, and 7 days after the emergence of spring rape: r = –0.81, P ≤ 0.05; r = –0.88, P ≤ 0.01.
Rapeseed (Brassica napus L.) belongs Brassicaceae family is the second most important oilseed crop in Pakistan after cotton. It contains 40-46% oil content and 22% protein. There are several factors which lowers seed yield like abiotic and biotic stresses.Alternaria blight and white rust diseases are the major threat for reducing Brassica seed yield in Pakistan. White Rust (WR) is the most destructive disease of brassica in tropical and subtropical areas of Pakistan caused by Albugo candida. It causes 20-90% yield losses throughout the world. In Pakistan, it was first reported from FATA and BAJAUR Agency with 32% pod losses and 52% foliage losses. A. candida is an obligate parasite and its survival rate is very high in plants debris and soil. It is reported from different Asian and European countries causing different epidemics. It has wide host range of Cruciferae, Ficoidaceae, Cappaaracea, and Cleeeomaceae white or off-white (creamy) raised pustules of pin size to various forms and sizes leading to stag-head formation. Three types of spores are produced and their nature of infection is variable. Oospores are seed and airborne when carried on seed,or overwintered in soil; serve as prime source of infection in Brassica. Through extensive research different races of A. candida are identified on different host range. Few races like AC 2, 3, 4, 5, 6, 7, 8, 9 are common in various countries and different researcher named them accordingly. That’s why it is being placed in different families, and genera. Infection of pathogen brings different biochemical changes in plant. These changes in host are useful to understand the biochemistry, host pathogen -interaction and to manage the disease by avoiding symptom’s ambiguity. Screening of resistant germplasm is a prime factor and extensive research is being conducted in this regard. Resistant cultivars are the best option to control the disease as they are eco -friendly, locally adapted to the environment, and durable. Different genotypes of Brassica juncea, B. carinata, B. napus and B. rapa were evaluated in field conditions against white rust for five years. Resistant sources are mentioned in this review according to the local climate of different countries. Chemicals protect the plants by forming layer on leaves surface while some have ability to penetrate the system and help the plant to reverse the biochemical changes induced by the pathogen. The Symptomology of a disease plays an imperative role in the understanding of altered physiological changes and the establishment of pathogen within host but there are many factors which caused the symptoms uttered by pathogenic fungus like infection time, type of infection, plant age, genetic makeup of the host plant and environmental conditions which need further research. Biochemical changes play an important role in the plant defense and induce resistance as the proteins form complex with fungus to inhibit it. One compound regulates the level of other one in tissues as H2O2 is produced at a very high rate in susceptible but less in moderately resistant lines. As a defensive action on H2O2 the quantity of CAT which led to increase in POD and SOD is increased to manipulate later and so is the way of regulating it. Catalase (CAT) prevents the accumulation of H2O2 in the cells. CAT activity increases in resistant varieties and it breaks down the hydrogen peroxide into water and oxygen. Peroxidase (POD) plays a significant role in defense response and its activity is associated
with resistance induction in different species of plants. It is also involved in the breakdown of hydrogen peroxide. Increased activity of peroxidase leads to the production and accumulation of hydroxyproline rich glycoprotein into the cell wall. Peroxidase is involved in lignin polymerization. The enzyme has a role in cell wall metabolism as well as in defense regulation and induction. Superoxidase dismutase enzyme acts as a first line of defense against reactive oxygen species (ROS) and rapid induction of SOD leads to recognize the pathogen’s avirulence factors. phenolic contents can be increased due to glycosidic esters formed by the enzymatic activity of host or pathogen or due to migration of phenols from uninfected tissue. Our research findings support the above
mentioned facts. Different researcher has reported different chemicals of same formulations as Meralaxyl, Mancozeb, Captaf, Swing and Atracol to control white rust either using them as seed treatment or foliar
application. These biochemical and chemicals interactions need more exploration.
Time series prediction of pest and natural enemies is most important for the crop management and minimizing the pesticide use and the Artificial neural network (ANN) model is most powerful Artificial intelligence (Al) machine learning models have the capacity to generalize more with less error and it is also important to investigate the convergence of the Back propagation (BP). In the present study separate and efficient neural network model was developed for Gall Midge, Brown Plant Hopper and Damsel fly and the model performance criteria such as RMSE, RMAE, CC, MEF, AIC and BIC was calculated for each stage and compared. Performance of the network at training, validation and testing stage checked using different number of epochs with minimum learning rate (0.01). Selection of best architecture was made based on Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), that network with less AIC and BIC value were selected and which is free from over fitting. Therefore ANN methodology could be used to predict the incidence of pests and damsel fly (Natural enemy) for better management practice well in advance and to avoid the environmental pollution due to more use of chemical pesticides.
Oilseed Brassica also referred as rapeseedmustard, is the second most important edible oilseed crop in India after groundnut and accounts for nearly 30% of the total oilseeds produced in the country. The oleiferous Brassicas including Brassica juncea (L) Czern & Coss., B. rapa (syn. B. campestris L.) and B. napus L. are the important sources of edible oil in India. When compared to other edible oils, the rapeseed-mustard oil has the lowest amount of harmful saturated fatty acids. It also contains adequate amounts of the two essential fatty acids, linoleic and linolenic, which are not present in many of the other edible oils. Canada is the largest exporter of rapeseed-mustard, Australia follows Canada. The major importing countries are US, Japan and Mexico. Countries like China, India, Canada, Japan, Mexico, US and European Union, which consume rapeseed-mustard oil cake extensively that is mainly used as cattle feed. Rapeseed-mustard is cultivated all over the world mainly under rainfed conditions with low input management during rabi (post-rainy) season. Rapeseed-mustard group of crops are basically temperate crops. They perform well on loamy soils having pH around 7. The temperature range of 0.5 to 3 o C, 20 to 35 o C and 35 to 40 o C can be considered to be minimum, optimum and maximum, respectively for these crops. The productivity of rapeseed-mustard was 1145 kilogram/ hectare (kg/ha) as compared to 1135 kg/ ha of total oilseeds which was 854 kg/h during 2002-03. There are varieties like NRCDR-601 has been developed having the highest potential yield 3723 kg/ ha so far (Chauhan et al., 2012). Why there exists a gap between production potential and actual realization in India? In India research is in its infancy as compared to developed countries. The major issues could be • Lack of proper crop cultivation practices and harvesting methods. • Lack of quality seed. • Reduced soil fertility due to repeated sowing.
Training addressed the recent advances in oilseed Brassica plant pathology particularly on various aspects of plant disease management through lectures, practical and field visits. Scientific areas covered including diagnostics, IDM, pathogen diversity, epidemiology, resistance breeding, cultural practices, conventional and molecular approaches etc.
We are highly grateful to Prof. Arvind Kumar, Hon’ble Vice Chancellor, Rani Lakshmi Bai
Central Agricultural University, Jhansi for his constant support, guidance and encouragement in making the training a great success. We gratefully acknowledge the help and guidance received from Dr. N.S. Rathore, DDG (Edn) & Dr. M. B. Chetti, ADG (HRD), ICAR. We would be failing in our duty if we do not put on record the help and guidance received from Dr. Dhiraj Singh, Director, DRMR in conducting the proceedings of the training through practical and field visits.
Alternaria blight of crucifers occurs and develops in the epidemic form under the combination of a number of factors including availability of susceptible host cultivars, source of virulent pathogen inoculum in the vicinity, and favourable environmental and cultural conditions. Temperature range of 15–25 °C, relative humidity >90 %, wind velocity of 2–5 km/h, and intermittent rains are the most abiotic conducive conditions for development of Alternaria blight under field conditions. In addition, closer spacing of 30 × 15 cm, high doses of nitrogen (>80 kg/ha), frequent irrigation and growing of susceptible cultivars further rapidly increase the disease severity in rapeseed–mustard. The disease progression under field conditions as influenced by environmental conditions and dates of sowing has been measured through the development of models. Disease forecasting models have been developed taking into account the leaf wetness period; number of rainy days; minimum, maximum and optimum temperatures and relative humidity; date of sowing; variety and species of Brassica crops grown under different agro-ecological conditions.
Epidemiology deals with the dynamics of plant pathogens infecting host populations, while epizoology is relevant for insect pests. Bitter memories of the Irish famine and potato late blight motivated plant pathologists to probe the reasons behind the same. They looked at the biology of the pathogen, its life cycle, host–pathogen systems, etc. The eradication of barberry plants (Mehta, 1933) marked the beginning of phytoepidemiological awareness for plant disease management. “Dutch rules”, the first national blight-forecasting system, proposed by van Everdingen (1926) for potato late blight prediction is still relevant today since recent systems consider the same meteorological parameters indicated in that forecasting system. Gradually, meteorologists (Schröeder, 1960; Bourke, 1970), aerobiologists (Hirst, 1952; Gregory, 1968), mathematicians (Vanderplank, 1963), and other phytopathologists (Waggoner and Horsfall, 1969) joined the bandwagon. Waggoner and Horsfall (1969) simulated plant disease epidemics on a computer, while Vanderplank (1963) viewed practical epidemiology and forecasting of plant diseases as a multidisciplinary science. Post-Mehta, the world saw how Nagarajan and Singh (1990) discovered that wheat rust epidemics over the Indian subcontinent are influenced by western disturbance of air and depressions that pass over the Nilgiri Hills. Spores of wheat stem rust travel from south India to central and north India. Monitoring ambient conditions with western disturbance by weather satellites over northwest India between November and April could be used as an index to discover whether it will be a year for brown rust, yellow rust, or no rust (Nagarajan and Singh, 1990).
Incidence and severity of white rust (WR) varies from year to year on different crops. Factors affecting initiation and development of the disease have not been studied in detail. On spinach, sporangial production is profuse at low temperatures but oospore production is very abundant at higher temperatures (Raabe and Pound, Phytopathology 42:473, 1952a, Phytopathology 42:448–452, 1952b). On water spinach in Hong Kong, during the main growing season (May to October), temperatures of 24–29 °C with heavy dew formation is ideal for infection and disease development (Edie and Ho, Trans Br Mycol Soc, 55:205–216, 1970). On sunflower in Australia, WR development is greatest between 20–25 °C (Kajomchaiyakul and Brown, Trans Br Mycol Soc, 66:91–95, 1976). Sempio (Riv Pat Veg, 28:393–397, 1938, Riv Pat Veg, 30:29–64, 1940) reported that the optimum temperatures for the development of WR on potted radish plants were 16–18 °C, with a range of 12–21 °C; the disease did not develop below 6–7 °C or above 28–29 °C. Relative humidity (RH) of 60–80 % was more favourable than a saturated environment, CO2 between 70 and 80 mm, and Hg (9.6–11 %) inhibited disease development. The fungus was highly sensitive to the effect of ultraviolet light; the optimum dose for inhibition of disease was 25–30 min. WR of horseradish is most favoured at 15–20 °C (Takeshita, Dissertation Abstracts, 14:1493–1494, 1954). On Amaranthus species, ideal condition for the spread of WR around Delhi (India) occurs from October to the end of February. During this period, warm days with low humidity facilitate desiccation of sporangia while cool temperatures and heavy dew deposition at night provide optimum conditions for sporangial germination and infection (Mishra and Chona, Indian Phytopath, 16:333–343, 1963).
White rust caused by the fungus Albugo is the most devastating disease known to occur in more than 50 countries and infects about 400 plant species belonging to 31 families worldwide including important vegetable crucifers, oil yielding Brassicas, ornamental plants and numerous weeds. This book on "White Rust deals with the aspects on "the disease" and "the pathogen" is vividly illustrated for stimulating, effective and easy reading and understanding. We are sure that this comprehensive treatise on "white rust" will be of immense use to the researchers, teachers, students and all others who are interested in the diagnosis and management of white rust diseases of crops worldwide.
There is considerable loss in the yield of the crops as well as quality of produce due to the infestation of various pests and diseases. Such losses can be reduced to a considerable extent if their occurrence is known in advance so that timely remedial measures may be taken. Thus there is a need to develop forewarning systems which can provide advance information for outbreak of pests/diseases attack. Weather plays vital role in development of pests and diseases infestation in crops, therefore, a technique for forewarning pests/diseases may be obtained on the basis of weather variables. Most of the earlier workers have utilised regression models (both linear and non linear) for pests/diseases forewarning. Recently artificial neural network (ANNs) techniques have become the focus of much attention, largely because of their wide range of applicability and the ease with which they can treat complicated problems even if the data are imprecise and noisy. From statistical perspective, neural networks are interesting because of their potential use in prediction. This methodology has been explored for forewarning Alternaria blight in mustard for maximum disease severity, crop age at first appearance of disease and crop age at maximum disease severity as response variables and weather indices as predictors for three locations namely Bharatpur, Dholi and Berhampur. In this study, two types of neural network architectures namely Multilayer perceptron (MLP) and Radial basis function (RBF) were attempted and compared with weather indices based regression model and it has been found that a MLP performs best in terms of mean absolute percentage error (MAPE).
Recently artificial neural networks (ANNs) techniques has become the focus of much attention, largely because of their wide range of applicability and the ease with which they can treat complicated problems even if the data are imprecise and noisy. From statistical perspective, neural networks are interesting because of their potential use in prediction. This methodology have been illustrated by considering various aspects, viz maximum pest disease severity, crop age at first appearance of disease, crop age at maximum disease severity for powdery mildew in mustard crop at S K Nagar (Gujarat) as response variable and weather indices (a technique based on relatively smaller number of manageable variables and at the same time taking care of entire weather distribution) as predictors. In this study, data have been taken from Mission mode project under National Agricultural Technology Project, entitled 'Development of weather-based forewarning system for crop pests and diseases', CRIDA, Hyderabad in which the IASRI was one of the cooperating institutions. Two type of neural network architecture namely Multilayer perceptron (MLP) and Radial basis function (RBF) were attempted and compared with weather indices based regression model and it has been found that a MLP performs best in terms of mean absolute percentage error (MAPE).
Alternaria brassicae causes dark leaf and pod spot in Cruciferae. Epidemics of the disease were studied in the medium- term field trials of winter and spring oilseed rape (Brassica napus; WOSR, SOSR) as well as in spring turnip rape (Brassica rapa, STR) in 2000-2006 and in 2000-2003, respectively. Final disease incidence (FDI), final disease severity (FDS) and area under disease progress curve (AUDPC) values on pods were significantly affected by the cropping season (p < 0.001) and by fungicide application (p < 0.001). Disease incidence and severity were significantly higher in wet seasons (2000 and 2001 for winter, spring oilseed rape and spring turnip rape, 2004 for spring oilseed rape) than in dry (2002 and 2003) or very dry (2006) cropping seasons. The correlation between final disease severity on the leaves (middle, upper) and final disease severity on pods was moderate and highly significant (p < 0.01) in all Brassica crops. The correlation between final dark pod spot incidence and cumulative rainfall during pod development and ripening growth stages in Brassica crops (pooled data) was moderate (r s = 0.568; p < 0.05), however final disease severity and AUDPC values on pods showed strong and highly significant correlation with cumulative rainfall (r s = 0.715 and r s = 0.742, respectively; p < 0.01) and with relative humidity (r s = 0.787 and r s = 0.781, respectively; p < 0.01) during pod development and ripening growth stages. The results of this study provide means for predicting dark spot disease progression on the pods based on disease parameters on the middle and upper leaves in relation to meteorological conditions.
Qualitative and quantitative models were developed for damage due to podfly (Melanogromyza obtusa) on late maturing pigeonpea [Cajanus cajan (L.) Millsp] in Kanpur. Historical data from 1987-88 to 2009-10 on per cent pod damage and weekly weather variables were considered for model fitting. Weather based indices were generated which were used as explanatory variables. Models were validated on subsequent periods (2010-11 and 2011-12) data and found to be satisfactory for both qualitative (epidemic/non-epidemic year) and quantitative (extent of damage) forewarning of damage due to podfly in late pigeonpea at Kanpur.
Effect of climate change on agriculture or more precisely on insect pests and diseases of agricultural crops is multidimensional. Magnitude of this impact could vary with the type of species and their growth patterns. The elevated production could be offset partly or entirely by the insect pests, pathogens or weeds. It is, therefore, important to consider all the biotic components under the changing pattern of climate. World over research on effect of climate change on insect pests and diseases of crops is inadequate. Several diseases, insect pests and nematodes have been noted to be showing higher level of infestation on different field and horticultural crops in India, which have been discussed. The article also looks at different strategies to cope with effects of climate change on insect pests and diseases of crops with a proposal for Integrated Decision Support System (IDSS) for Crop Protection Services that suggest the operational focus, research priorities and aspects of capacity building.
Various models to study the effects of weather variables on rice yield at different stages of crop growth and to forecast its yield for Puri district have been attempted. The results indicated that above average maximum daily temperature had beneficial effects during ripening stage; detrimental effects during reproductive stage of the crop while in the initial growth, active and lag vegetative phase effects were fluctuating. The effect of increase in minimum temperature, was beneficial during initial, lag vegetative and reproductive stages, detrimental during ripening stage and fluctuating during active vegetative stage. Above average relative humidity and rainfall had beneficial effects throughout the growth and detrimental effects during ripening phase of the crop in general. The effects of rainfall and increase in number of rainy days were fluctuating up to lag vegetative, beneficial during reproductive and detrimental during ripening stage of the crop. Effects of increase in sunshine hours were detrimental during initial growth, active vegetative and reproductive stages, fluctuating during lag vegetative and beneficial during ripening stage of the crop.
A field experiment was laid out at S. K. Nagar and Bharatpur with Indian mustard (Brassica juncea) cultivars 'Varuna' and Local ('GM-2' at S. K. Nagar; 'PCR-7' at Bharatpur) sown on 10 dates at weekly intervals. Each plot was 1.5 m x 5 m size with a spacing of 30 cm x 10 cm. Recommended doses of N and P fertilizers were applied with no application of K fertilizer; insect-pest protection practices were undertaken viz., seed treatment with imidachloprid (5 g/kg) and spray 0.25 ml/l oxydematon-methyl at 15-day intervals. No protection was taken against any disease. First appearance of powdery mildew disease (Erysiphe cruciferarum) on leaves of mustard occurred during 50-120 days after sowing (d. a. s.), with higher frequencies in later part of the crop period. Severity of the disease was favoured by > 5 days of ≥ 9.1 h of sunshine, > 2 days of morning (maximum) relative humidity (r. h.) of < 90 %, afternoon (minimum) r. h. 24-50 %, minimum temperature > 5°C and a maximum temperature of 24-30°C. Regression analysis showed maximum temperature, minimum (afternoon) r. h. of the week preceding the date of observation were respectively positively and negatively correlated to disease severity both in cvs. 'Varuna' and 'GM-2' within the specified ranges. Models based on weather 1 week preceding date of observation for prediction of progression of powdery mildew severity at S. K. Nagar and Bharatpur were devised. Regional and cultivar-specific models could predict the crop age at which powdery mildew first appears on the crop, the highest mildew severity on the crop and the crop age at peak mildew severity at least 3 weeks ahead of first appearance of the disease on the crop, thus allowing growers to undertake timely fungicidal sprays. Models that stood the test of validation are reported.
Alternaria brassicae lesions on siliqua was found directly associated with the seed infection. Intensity of seed infection, varied with the number of lesions on a siliqua. Association of A. brassicae has been demonstrated with seeds of three crops of rape seed and mustard. however the population of the colonies of A. brassicae diminished with increased storage temperature and period. Temperature played a key role in survi- val of A. brassicae than storage material and period. A. brassicae survived with plant debris burried in field below the depth of 7.5 cm. Chenopodium alba has been recor- ded as a collaterial host of A, brassicae in field.
Fungicides mancozeb and carbendazim caused 100% reduction in mycelial growth of Alternaria brassicae over control in vitro while 1% (w/v) aqueous bulb extract of Allium sativum and leaf extract of Acacia nilotica caused significant reductions. In dual culture, GR isolate of Trichoderma viride performed the best among the test isolates of Trichoderma, causing 81%, 82% reduction in mycelial growth of A. brassicae over control. Performance of isolates SI-2, P and SI-1 of T. viride were at par (P < 0.01) with that of GR isolate. Spraying of A. brassicae at different ages of the mustard host plant identified 75 days after sowing (d.a.s.) as the most critical age of the mustard plant for development of Alternaria blight severity on the crop with 45 d.a.s. being the next most important one. Mancozeb was the best among all the treatments, resulting in the lowest disease severity on leaves of mustard at both Sewar and Ludhavai as also the lowest A-value (area under disease progress curve). Performance of bulb extract of A. sativum in checking the disease severity on leaves and pods was at par (P < 0.05) with mancozeb. The GR isolate of T. viride was at par with mancozeb in checking blight severity on mustard leaves at Sewar while performance of the bioagent was significantly (P < 0.05) inferior to the chemical fungicide at Ludhavai. Performance of the bioagent isolate GR of T. viride in checking the disease severity on pods was at par (P < 0.05) with mancozeb at both Sewar and Ludhavai, the treatment recording the lowest A-value on pods. While application of bulb extract of A. sativum resulted in highest seed yield at Sewar in 2001–2002, the bioagent isolate GR of T. viride did so at Ludhavai, both the treatments being at par (P < 0.05) with mancozeb and significantly higher than control. Application of bulb extract of A. sativum at 45 and 75 d.a.s. resulted in lowest blight severity on leaves and pods as also in highest seed yield among the different single and combination of treatments. Although disease severity in the treatment was at par (P < 0.05) with that in mancozeb, application of the plant extract at the two stages of crop growth resulted in significantly higher seed yield compared with the two applications of the chemical fungicide. However, application of the treatments singly only at 75 d.a.s., GR isolate of T. viride at 45 and 75 d.a.s., A. sativum 45 d.a.s. + T. viride 75 d.a.s., and T. viride 45 d.a.s. + A. sativum 75 d.a.s. resulted in seed yield at par (P < 0.05) with application of bulb extract of A. sativum at 45 and 75 d.a.s.
Sporulation in A. brassicae and A. brassicicola on naturally-infected leaf discs of oilseed rape and cabbage required humidities equal to or higher than 91.5% and 87% r.h. respectively. The optimum temperatures for sporulation were 18–24°C for A. brassicae and 20–30°C for A. brassicicola at which temperatures both fungi produced spores in 12–14 h. Above 24°C sporulation in A. brassicae was inhibited. At sub-optimal temperatures sporulation times for A. brassicicola were significantly longer than for A. brassicae with the differences increasing with decrease in temperature. Interrupting a 16-h wet period at 20°C with a period of 2 h at 70% or 80% r.h. did not affect sporulation in either fungus but a dry interruption of 3–4 h inhibited sporulation in both. Exposure of both fungi to alternating wet (18 h at 100% r.h., 20°C) and dry periods (6 or 30 h at 5565% r.h., 20°C) did not affect the concentration of spores produced in each wet period. Sporulation times were not affected by either the host type of the age of the host tissue. White light (136 W/m2) inhibited sporulation in A. brassicae with the degree of inhibition increasing with increasing light intensity. The effect of light on sporulation in A. brassicicola was not tested.
In controlled environment experiments, when oilseed rape pods or leaves were inoculated with spore suspensions of Alternaria brassicae, the maximum disease incidence (proportion of pods or leaves diseased) increased as wetness period after inoculation increased from 4 to 24 h and as temperature increased to 20°C. There was a clear relationship between disease incidence on pods and incidence on leaves with the same wetness/temperature conditions. Logistic equations described the effects of wetness period after inoculation on disease incidence (number of pods or leaves infected) or disease severity (number of lesions on pods or leaves) using temperature-dependent and tissue-dependent parameters. The time from inoculation to the appearance of the first lesions was shorter on pods than on leaves at temperatures ≤15°C and wetness periods ≤12 h. Two-dimensional response surface equations or simple interpolations from one-dimensional equations were used to develop contour maps of expected disease incidence and severity, respectively, on leaves or pods to estimate the effects of different combinations of wetness period during infection and temperature on disease development.
Pyrenopeziza brassicae, cause of light leaf spot of oilseed rape, has a complex polycyclic life cycle. It can be difficult to control light leaf spot in winter oilseed rape in the UK since it is not easy to optimise fungicide application timing. Early autumn infections are usually symptomless and recognisable lesions do not develop until the epidemic has progressed further by the spring. Light leaf spot often has a patchy distribution in winter oilseed rape crops and estimation of disease incidence can be difficult. There is evidence that epidemics are initiated primarily by ascospores produced from apothecia that survive the summer inter-crop period on infected debris. Subsequent development of the epidemic during the winter and spring is maintained by rain-splashed conidia that spread light leaf spot from initial foci. Understanding the relative roles of ascospores and conidia in the light leaf spot life cycle is crucial for forecasting epidemic severity and developing control strategies. The current web-based regional forecast system provides an autumn forecast of the incidence of light leaf spot that can be expected the following spring. This is based on survey data which assesses the occurrence of disease the previous July, and weather factors, such as deviations from summer mean temperature and winter rainfall. The forecast can be updated throughout the autumn and winter and includes crop-specific elements so that growers can adjust risks by inputting information about cultivar, sowing date and fungicide use. Crop-specific forecasts can be confirmed by assessing the incidence of light leaf spot. Such assessments will become easier when immunodiagnostic methods for detection of the disease become available. Incorporation of information on spore biology (e.g. apothecial maturation, ascospore release and infection conditions) is considered as a component of the interactive, continuously updated, crop-specific, web-based forecasts which are needed in the future.
Resistance in susceptible mustard cv. PR-15 against the highly virulent A. brassicae isolate A (AbA) and moderately virulent isolate C (AbC) was induced using an avirulent Alternaria brassicae isolate D (AbD). The induction of resistance due to AbD against AbA or AbC resulted in significant reduction in disease severity. The A. alternata (Aa) failed to induce resistance against AbA and AbC, on the contrary it induced susceptibility against them.
Genetic variation in Alternaria brassicae, A. brassicicola, and A. raphani collected from geographically diverse regions of the world was studied with RAPD and RFLP markers. Twenty 10-mer primers of arbitrary nucleotide sequences were tested for amplification of genomic DNA of A. brassicae using PCR. Of these, five primers amplified the genomic DNA from 20 A. brassicae isolates and produced reproducible RAPD profiles. UPGMA analysis of RAPD data showed that isolates collected from geographically distinct regions could be broadly classified into four groups. Intra-regional variation between isolates was less apparent. Variation was, however, higher in A. brassicicola, as based on RAPD analysis. Two isolates (from Canada and France) of A. raphani also showed variability with different RAPD profiles generated by all five primers tested. Five polymorphic, distinct RAPD products were used as hybridization probes for RFLP analysis to detect inter- and intra-specific variation. Variation among A. brassicae, A. brassicicola, and A. raphani was evident. Non-radioactive probes were also used to hybridize with Southern blots of A. brassicae, A. brassicicola, Leptosphaeria maculans, Rhynchosporium secalis and Brassica juncea for the selection of A. brassicae-specific probe(s). Probe AbP3 specifically hybridized with restriction digests of A. brassicae but not with those of A. brassicicola or other tested species. This probe should, therefore, be useful for distinguishing between two important pathogens of crucifers, i.e. A. brassicae and A. brassicicola both in culture and infected tissues.
Phoma stem canker (blackleg), caused by Leptosphaeria maculans, is an important disease on oilseed rape (canola, rapeseed, Brassica napus, Brassica juncea, Brassica rapa) causing seedling death, lodging or early senescence in Australia, Canada and Europe, but not in China. The two forms of L. maculans (A group and B group) that occur on oilseed rape are now considered to be separate species. The epidemiology and severity of phoma stem canker differs between continents due to differences in the pathogen population structure, oilseed rape species and cultivars grown, climate and agricultural practices. Epidemics are most severe in Australia, where only the A group occurs, and can be damaging in Canada and western Europe, where both A and B groups occur, although their proportions vary within regions and throughout the year. Epidemics are slight in China, where the A group has not been found. Dry climates (Australia, western Canada) lengthen the persistence of infected debris and may synchronize the release of airborne ascospores (after rain) with seedling emergence. L. maculans spreads from cotyledon and leaf infections down petioles to reach the stem, with infections on cotyledons and leaves early in the season producing the most damaging stem cankers at the stem base (crown). Development of both crown cankers and phoma stem lesions higher up stems is most rapid in regions with high temperatures from flowering to harvest, such as Australia and Canada. Breeding for resistance (genetic, disease escape or tolerance), stubble management, crop rotation and fungicide seed treatments are important strategies for control of phoma stem canker in all areas. Fungicide spray treatments are justified only in regions such as western Europe where high yields are obtained, and accurate forecasts of epidemic severity are needed to optimize their use.
Effect of some factors on growth and sporulation of Alternaria brassicae causing Alternaria blight of rapeseed and mustard
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Relationship of disease severity and yield due to leaf blight of mustard and spray schedule of mancozeb for higher benefit
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