scholarly journals Evaluation of BSPcast Disease Warning System in Reduced Fungicide Use Programs for Management of Brown Spot of Pear

Plant Disease ◽  
2000 ◽  
Vol 84 (6) ◽  
pp. 631-637 ◽  
Author(s):  
I. Llorente ◽  
P. Vilardell ◽  
R. Bugiani ◽  
I. Gherardi ◽  
E. Montesinos
Keyword(s):  
Disease Management ◽  
Disease Incidence ◽  
Warning System ◽  
Growing Season ◽  
Infection Risk ◽  
Brown Spot ◽  
Forecasting Model ◽  
Advisory System ◽  
Application Programs ◽  
Protection Period

A forecasting model (BSPcast) developed for prediction of brown spot (Stemphylium vesicarium) of pear was evaluated as an advisory system for reduced fungicide use in disease management programs. Eleven trials were performed during 1995, 1996, and 1997 in five orchards in two different climatic areas in Catalunya (Spain) and Emilia-Romagna (Italy). Values of 3-day cumulative daily infection risk (CR) provided by the model were used to determine risk periods during the growing season of pear and were taken as thresholds to schedule fungicide sprays. The fungicide application programs tested using the model consisted of guided schedules with CR action thresholds of 0.4, 0.5, or 0.6, and fixed sprays following a standard commercial schedule. In nine out of 10 trials, no significant differences were observed in disease incidence on fruit at harvest between the fixed-spray commercial schedule and guided sprays using thresholds of 0.4 or 0.5. The average savings in number of fungicide sprays applied using BSPcast compared with the fixed-spray schedule were 20 to 70% when using fungicides with a 15-day protection period (kresoxim-methyl or procymidone) and ranged from 20 to 50% when using a fungicide with a 7-day protection period (thiram).

scholarly journals A review on important maize diseases and their management in Nepal

2015 ◽  
Vol 1 (1) ◽  
pp. 28-52 ◽  
Author(s):  
Subash Subedi
Keyword(s):  
Disease Management ◽  
Disease Incidence ◽  
Bacterial Species ◽  
Gray Leaf Spot ◽  
Leaf Blight ◽  
Brown Spot ◽  
Steady Increase ◽  
Ear Rot ◽  
Loss Assessment ◽  
Maize Crop

In Nepal, maize ranks second after rice both in area and production. In recent years, maize area and production has shown a steady increase, but productivity has been low (2.46 t/ha). The major maize producing regions in Nepal are mid hill (72.85%), terai (17.36%) and high hill (9.79%) respectively. A literature review was carried out to explore major maize diseases and their management in Nepal. The omnipresent incidence of diseases at the pre harvest stage has been an important bottleneck in increasing production. Till now, a total of 78 (75 fungal and 3 bacterial) species are pathogenic to maize crop in Nepal. The major and economically important maize diseases reported are Gray leaf spot, Northern leaf blight, Southern leaf Blight, Banded leaf and sheath blight, Ear rot, Stalk rot, Head smut, Common rust, Downy mildew and Brown spot. Information on bacterial and virus diseases, nematodes and yield loss assessment is also given. Description of the major maize diseases, their causal organisms, distribution, time and intensity of disease incidence, symptoms, survival, spreads, environmental factors for disease development, yield losses and various disease management strategies corresponded to important maize diseases of Nepal are gathered and compiled thoroughly from the available publications. Concerted efforts of NARC commodity programs, divisions, ARS and RARS involving research on maize pathology and their important outcomes are mentioned. The use of disease management methods focused on host resistance has also been highlighted.Journal of Maize Research and Development (2015) 1(1):28-52DOI: http://dx.doi.org/10.5281/zenodo.34292

scholarly journals Status of Rice Brown Spot (Helminthosporium oryza) Management in India: A Review

2021 ◽  
Author(s):  
M. Surendhar ◽  
Y. Anbuselvam ◽  
J. Johnny Subakar Ivin
Keyword(s):  
Disease Management ◽  
Yield Loss ◽  
Disease Incidence ◽  
Control Measures ◽  
Brown Spot ◽  
Strong Impact ◽  
Management Protocol ◽  
Current Scenario ◽  
Helminthosporium Oryzae ◽  
Historic Significance

Rice is one of the most widely consumed staple food for more than half of the population in the world. Brown spot caused by Helminthosporium oryzae accounts for 5% yield loss worldwide annually. Adversely affected fields show yield loss as high as 45%. The present study focuses on the several management aspects that are currently used to curb out the disease incidence and measures to be taken in near future for designing effective disease management protocol. The disease is of historic significance and a devasting outbroke in the Bengal Province during 1943 ended as the Great Bengal Famine resulting in starvation and an estimated demise of 2.1 to 3 million people. Brown spot is still devastating on looking the present scenario of damage to rice. Different approaches have been adopted ranging from the use of brown spot resistant rice cultivars, chemical ameliorations and biological control measures for the management of the disease. But, still the disease seems to be chronic and adverse in the current scenario. In this review, we have highlighted epidemiology, control measures practiced and several quantitative and qualitative gaps with respect to disease management, which if rectified, would lead to a strong impact on crop disease control and the sustainable Rice production that are pertinent to the present situation of farmers.

scholarly journals Quantitative Detection of Pear-Pathogenic Stemphylium vesicarium in Orchards

2009 ◽  
Vol 99 (12) ◽  
pp. 1377-1386 ◽  
Author(s):  
J. Köhl ◽  
B. H. Groenenboom-de Haas ◽  
P. Kastelein ◽  
V. Rossi ◽  
C. Waalwijk
Keyword(s):  
Crop Residues ◽  
Dynamic Range ◽  
Disease Incidence ◽  
Quantitative Polymerase Chain Reaction ◽  
Growing Season ◽  
Control Measures ◽  
Brown Spot ◽  
Quantitative Detection ◽  
Stemphylium Vesicarium ◽  
Taqman Pcr

Isolates of Stemphylium vesicarium causing brown spot of pear can be distinguished from nonpathogenic isolates of S. vesicarium from pear or from other hosts on the basis of distinctive amplified fragment length polymorphism fingerprinting profiles. DNA fragments specific for isolates pathogenic to pear were identified and a quantitative polymerase chain reaction (PCR) was developed on the sequence from one of these specific DNA loci. This TaqMan PCR has a high sensitivity with a dynamic range for reliable quantification between 1 ng and 100 fg of DNA. The method detected pear-pathogenic isolates of S. vesicarium originating from four different European countries and various regions within those countries. No cross-reaction was found with either the nonpathogenic isolates of S. vesicarium tested or isolates belonging to other Stemphylium spp. or related fungi. The pathogen was detected on leaves with brown-spot symptoms originating from six different locations in The Netherlands, Italy, and Spain. Pear-pathogenic S. vesicarium populations were monitored on crop residues in two Dutch orchards between October 2007 and October 2008. Brown spot had been observed at both orchards at the end of the growing season of 2007. In one location, pear-pathogenic S. vesicarium was detected only sporadically on crop residues and no brown-spot symptoms were observed on fruit in 2008. At the other location, a pathogenic population was found on fallen pear leaves and on other crop residues but this population decreased during winter. From the beginning of the growing season in 2008 onward, the pathogen population could not be detected and the disease incidence was only 0.6%. The TaqMan PCR will allow more detailed studies on epidemiology of brown spot and on the effect of disease control measures.

scholarly journals SPATIAL DISTRIBUTION OF EARLY BLIGHT DISEASE ON TOMATO, CLIMATIC FACTORS AND BIOEFFICACY OF PLANT EXTRACTS AGAINST Alternaria solani

2019 ◽  
Vol 18 (6) ◽  
pp. 29-38
Author(s):  
Azhar Hussain ◽  
Shaukat Ali ◽  
Haider Abbas ◽  
Haibat Ali ◽  
Alamdar Hussain ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Disease Management ◽  
Plant Extracts ◽  
Early Blight ◽  
Interpolation Method ◽  
Disease Incidence ◽  
Alternaria Solani ◽  
Growing Season ◽  
Growing Seasons ◽  
Blight Disease

Information on the spatial variability in plant disease is essential for location-based disease management. In the current study, the spatial distribution of tomato early blight disease was ascertained in District Gilgit, GilgitBaltistan, Pakistan. The comprehensive field survey was carried in two growing seasons (2014–2015), whereas in each growing season, 62 tomato fields were surveyed. Based on the distribution of disease, the respective thematic maps (incidence and severity) were prepared using Arc Map 10.1 with spatial analyst function of  Arc GIS software by means of the inverse distance weight (IDW) interpolation method. Results indicate that early blight of tomato is spatially distributed in both growing seasons. However, in the first growing season, the disease incidence ranged from 10.22% to 44.16% and during later season 14.03–49.16%, whereas 5.37–16.40% and 6.52–26.94% severity was recorded. Furthermore, this information indicates that higher disease infestation occurred in 2015 in relation to 2014. This information linked to metrological data (temperature, precipitation and relative humidity), seemingly favored the early blight development during the growing period. Seven botanical extracts were tested against pathogen Alternaria solani at different concentrations (4, 6 and 8%). Results revealed that all tested plant extracts showed antifungal activities. However, at 8% concentration of plant extract, Datura starmonium, Berberis orthobotry, Podophyllum emodi and Uretica dioica exhibited >60%, while Peganum harmala, Artemisia maritima and Capparis spinosa <60% antifungal properties. The information generated due to this study could help the tomato growers regarding disease management and selection of resistant cultivars, improving profitability and food security in the Gilgit region.

scholarly journals Investigation of Botrytis Cinerea Risk Forecasting Model of Strawberry in Lithuania

2013 ◽  
Vol 67 (2) ◽  
pp. 195-198 ◽  
Author(s):  
Neringa Rasiukevičiūtė ◽  
Alma Valiuškaitė ◽  
Elena Survilienė-Radzevičė ◽  
Skaidrė Supronienė
Keyword(s):  
Disease Management ◽  
Botrytis Cinerea ◽  
Air Temperature ◽  
Grey Mould ◽  
Management Systems ◽  
Forecasting Model ◽  
Leaf Wetness ◽  
Risk Of Infection ◽  
Risk Forecasting ◽  
Risk Probability

Grey mould, caused by Botrytis cinerea Pers.:Fr. is one of the most important strawberry diseases in Lithuania, like in other countries, where strawberries are grown. The efficiency of different disease management systems were analyzed at the Institute of Horticulture in 2010-2011. The B. cinerea risk probability at various regions of Lithuania was analyzed according to iMETOS ®sm grey mould risk forecasting model. Strawberry grey mould risk forecasting model indicates the risk of infection periods on the basis of the interaction between air temperature and leaf wetness duration. The model calculates how favourable is the period for the risk of infection. In periods where the risk is consistent (more than three days), higher than 60 points, a spray against grey mould should be applied. iMETOS®sm grey mould risk forecasting model gives the opportunity to optimize the usage of fungicides and reduce the number of applications and allows more efficient, ecologically and economically accepted control of strawberries grey mould.

scholarly journals Evaluation of a Disease Warning System for Downy Mildew of Grapes

Plant Disease ◽  
2000 ◽  
Vol 84 (5) ◽  
pp. 549-554 ◽  
Author(s):  
L. V. Madden ◽  
M. A. Ellis ◽  
N. Lalancette ◽  
G. Hughes ◽  
L. L. Wilson
Keyword(s):  
Linear Model ◽  
Downy Mildew ◽  
Environmental Conditions ◽  
Generalized Linear Model ◽  
Disease Incidence ◽  
Warning System ◽  
Plasmopara Viticola ◽  
Effective Control ◽  
Subsequent Infection ◽  
Grape Downy Mildew

An electronic warning system for grape downy mildew— based on models for the infection of leaves of Vitis lambrusca, production of sporangia by Plasmopara viticola in lesions, and sporangial survival—was tested over 7 years in Ohio. Grapevines were sprayed with metalaxyl plus mancozeb (Ridomil MZ58) when the warning system indicated that environmental conditions were favorable for sporulation and subsequent infection. Over the 7 years, plots were sprayed from one to four times according to the warning system, and from four to 10 times according to the standard calendar-based schedule (depending on the date of the initiation of the experiment). The warning system resulted in yearly reductions of one to six sprays (with median of three sprays). Disease incidence (i.e., proportion of leaves with symptoms) in unsprayed plots at the end of the season ranged from 0 to 86%, with a median of 68%. Incidence generally was very similar for the warning-system and standard-schedule treatments (median of 7% of the leaves with symptoms), and both of these incidence values were significantly lower (P < 0.05) than that found for the unsprayed control, based on a generalized-linear-model analysis. Simplifications of the disease warning system, where sprays were applied based only on the infection or sporulation components of the system, were also effective in controlling the disease, although more fungicide applications sometimes were applied. Effective control of downy mildew, therefore, can be achieved with the use of the warning system with fewer sprays than a with a standard schedule.

Studies on the behaviour of some fungal diseases of rice in the mangrove swamp ecology at Warri, south eastern Nigeria

2003 ◽  
Vol 51 (4) ◽  
pp. 429-436
Author(s):  
E. A. Maji ◽  
E. D: Imolehin
Keyword(s):  
Disease Incidence ◽  
Block Design ◽  
Rice Variety ◽  
N Fertilization ◽  
Brown Spot ◽  
Bipolaris Oryzae ◽  
Southeastern Nigeria ◽  
Mangrove Swamp ◽  
Main Plot ◽  
Cropping Seasons

Studies on the ecological behaviour of Cochliobolus miyabeanus (Ito et Kurib.) Drechsl. ex Dast., syn. Bipolaris oryzae (Breda de Haan Shoem.), the causal agent of brown spot in rice (Oryza sativa L.), were carried out in the tidal mangrove swamp at Warri Experimental Farm, Southeastern Nigeria. A split randomised complete block design with four replications was used. Monthly transplantings from July to September formed the main plot, which was subdivided into control and N-treated subplots. Disease incidence increased when transplanting was delayed. This was probably due to the fact that flowering coincided with environmental conditions favourable for disease development from November to February. Nitrogen fertilization at 40 kg N/ha significantly (P=0.05) reduced C. miyabeanus incidence in 1997/1998, but not in the 1998/1999 and 1999/2000 cropping seasons at the same site. The grain yields of ROK 5, a medium-duration improved rice variety (approx. 150 days), were significantly (P=0.05) reduced in late-transplanted crops (September to November) in spite of adequate N fertilization. Mangrove mud was not an important source of C. miyabeanus propagules. The incidence of leaf scald caused by Monographella albescens (Thum) Parkinson, Sivanesan and Booth syn. Microdochium oryzae (Hashioka and Yokogi) Samuels and Hallet, and of leaf smut caused by Etyloma oryzae Miyake was generally stimulated by N application.

Evaluation of the Florida Strawberry Advisory System for Control of Botrytis and Anthracnose Fruit Rots in Ohio

2018 ◽  
Vol 19 (2) ◽  
pp. 182-187 ◽  
Author(s):  
L. G. Cordova ◽  
M. A. Ellis ◽  
L. L. Wilson ◽  
L. V. Madden ◽  
N. A. Peres
Keyword(s):  
Disease Management ◽  
The Other ◽  
Fruit Rot ◽  
Leaf Wetness ◽  
Advisory System ◽  
Four Seasons

The Florida Strawberry Advisory System (StAS) forecasts the need for fungicide applications for control of Botrytis fruit rot (BFR) and anthracnose fruit rot (AFR) based on leaf wetness and temperature during the moist period. StAS was evaluated in Ohio for four seasons from 2011 to 2014 and compared with the calendar-based system currently used by growers. BFR was severe in 2011 and 2013 and nearly absent in the other years, whereas AFR was not a problem in any of the four years. Using the calendar-based system, five to six applications were made each year for BFR, whereas only two or fewer were recommended using StAS. For AFR control, six to seven applications were made based on the calendar system, whereas three or fewer were recommended by StAS. There was no case in which the calendar program outperformed the StAS in disease management. Use of StAS would greatly reduce the number of sprays needed for control of fruit rot diseases and result in significant savings for Ohio strawberry growers.

scholarly journals Incorporation of Temperature and Solar Radiation Thresholds to Modify a Lettuce Downy Mildew Warning System

2002 ◽  
Vol 92 (6) ◽  
pp. 631-636 ◽  
Author(s):  
B. M. Wu ◽  
A. H. C. van Bruggen ◽  
K. V. Subbarao ◽  
H. Scherm
Keyword(s):  
Solar Radiation ◽  
Downy Mildew ◽  
Disease Incidence ◽  
Characteristic Curve ◽  
Warning System ◽  
Effect Of Temperature ◽  
Photon Flux ◽  
Photon Flux Density ◽  
Leaf Wetness ◽  
High Solar Radiation

The effect of temperature on infection of lettuce by Bremia lactucae was investigated in controlled environment studies and in the field. In controlled conditions, lettuce seedlings inoculated with B. lactucae were incubated at 15, 20, 25, or 30°C during a 4-h wet period immediately after inoculation or at the same temperatures during an 8-h dry period after the 4-h postinoculation wet period at 15°C. High temperatures during wet and dry periods reduced subsequent disease incidence. Historical data from field studies in 1991 and 1992, in which days with or without infection had been identified, were analyzed by comparing average air temperatures during 0600 to 1000 and 1000 to 1400 Pacific standard time (PST) between the two groups of days. Days without infection had significantly higher temperatures (mean 21.4°C) than days with infection (20.3°C) during 1000 to 1400 PST (P < 0.01) but not during 0600 to 1000 PST. Therefore, temperature thresholds of 20 and 22°C for the 3-h wet period after sunrise and the subsequent 4-h postpenetration period, respectively, were added to a previously developed disease warning system that predicts infection when morning leaf wetness lasts ≥4 h from 0600 PST. No infection was assumed to occur if average temperature during these periods exceeded the thresholds. Based on nonlinear regression and receiver operating characteristic curve analysis, the leaf wetness threshold of the previous warning system was also modified to ≥3-h leaf wetness (≥0900 PST). Furthermore, by comparing solar radiation on days with infection and without infection, we determined that high solar radiation during 0500 to 0600 PST in conjunction with leaf wetness ending between 0900 and 1000 PST was associated with downy mildew infection. Therefore, instead of starting at 0600 PST, the calculation of the 3-h morning leaf wetness period was modified to start after sunrise, defined as the hour when measured solar radiation exceeded 8 W m-2 (or 41 μmol m-2 s-1 for photon flux density). The modified warning system was compared with the previously developed system using historical weather and downy mildew data collected in coastal California. The modified system was more conservative when disease potential was high and recommended fewer fungicide applications when conditions were not conducive to downy mildew development.

Early-Warning Model for TECC Based on Gray Neural Network - Taking Laolongtou Scenic Area as an Example

2013 ◽  
Vol 397-400 ◽  
pp. 2435-2438
Author(s):  
Xiu Ping Yang ◽  
Er Chao Li
Keyword(s):  
Neural Network ◽  
Early Warning ◽  
Early Warning System ◽  
Historical Data ◽  
Fuzzy Inference ◽  
Warning System ◽  
Forecasting Model ◽  
Error Signal ◽  
Single Feature ◽  
Warning Model

Based on fuzzy inference and gray neural network, indexes of early-warning system of carrying capacity in scenic spots is established and extract fuzzy rules based on historical data, simulate the early-warning system based on fuzzy inference, gray forecasting model is built for single feature index respectively, add a compensated error based on neural network. The prediction value equals to the output value of grey neural network model plus the compensated error signal. At last, takes Laolongtou scenic area as an example.

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