Potato Late Blight Disease Research Articles

Epidemiology of Late Blight of Potato, Its Progress and Apparent Rate of Infection

Late blight of potato caused by Phytophthora infestans is one of the most destructive diseases of potato world over. The devastation of the disease is very much related with climatic factors like temperature, relative humidity, fog or dew deposition and also sunshine hours. An experiment was conducted in Indo-Gangetic plains of West Bengal to know the effect of weather parameters on initiation and severity of the disease as well as progress and pattern of development of disease which will ultimately help to develop the effective spray schedule to manage the disease. From the experiment it is observed that 7 days prior to first appearance of late blight disease of potato the average maximum and minimum temperature varied between 24-26˚C and 7-8˚C respectively; average maximum and minimum relative humidity varied between 90-93% and 41-44% respectively; average sunshine hours per day varied between 6-8 hours. Correlation study of late blight disease severity with different weather parameters were also carried out. Maximum and minimum temperature as well as maximum and minimum relative humidity found to be positively correlated with late blight disease build up. While sunshine hour found to be negatively correlated with the disease build up. But only minimum temperature was significant at 0.01 level in all the planting dates and maximum temperature was significant at 0.01 level in two dates of planting. Apparent rate of infection of the disease and area under disease progress curve were calculated for different planting dates of potato. From the results it is evident that late blight of potato progressed almost in an exponential fashion starting from its first appearance. As the crop approached towards maturity and weather became unfavourable for the pathogen the rate of progress declined. This may be due to non-availability of healthy tissue.

Novel CropdocNet Model for Automated Potato Late Blight Disease Detection from Unmanned Aerial Vehicle-Based Hyperspectral Imagery

The accurate and automated diagnosis of potato late blight disease, one of the most destructive potato diseases, is critical for precision agricultural control and management. Recent advances in remote sensing and deep learning offer the opportunity to address this challenge. This study proposes a novel end-to-end deep learning model (CropdocNet) for accurate and automated late blight disease diagnosis from UAV-based hyperspectral imagery. The proposed method considers the potential disease-specific reflectance radiation variance caused by the canopy’s structural diversity and introduces multiple capsule layers to model the part-to-whole relationship between spectral–spatial features and the target classes to represent the rotation invariance of the target classes in the feature space. We evaluate the proposed method with real UAV-based HSI data under controlled and natural field conditions. The effectiveness of the hierarchical features is quantitatively assessed and compared with the existing representative machine learning/deep learning methods on both testing and independent datasets. The experimental results show that the proposed model significantly improves accuracy when considering the hierarchical structure of spectral–spatial features, with average accuracies of 98.09% for the testing dataset and 95.75% for the independent dataset, respectively.

Forecasting of Potato Late Blight Disease Using Alternative Sets of Meteorological Data and Disease Epidemiyology

Phytophthora infestans (Mont) de Bary, the causal agent of late blight of potato is one of the most important plant pathogens. The disease can occur in a wide variety of weather conditions and can be very devastating if no controlled. To reduce yield losses, different protective measures are used, including fungicide treatment. Uncontrolled and numerous fungicide applications cause environmental pollution. Accordingly, crop protection strategies optimizing the number of treatments are of great interest. Prediction of potato late blight epidemics, was studied in two different locations of Adana. Meteorological data (hourly) were recorded by an iMETOS® automatic weather station installed in the field and were compared with regional station Winstel, Blite Cast and Ullrich Schrodter models. Three disease warning models were compared to forecast the development of potato late blight in Adana between 2013 and 2014 first time. In the Çukurova region, the Winstel model yielded more accurate results in predicting infection conditions compared to the other two models. Studies provided that, the conditions of potato late blight disease formation in the region were determined and the use of the Winstel early warning system in accordance with the regional conditions and biotechnical methods which will be alternative to chemical control were provided by the regional farmers.

Spray-Induced Gene Silencing as a Potential Tool to Control Potato Late Blight Disease.

Phytophthora infestans causes late blight disease on potato and tomato and is currently controlled by resistant cultivars or intensive fungicide spraying. Here, we investigated an alternative means for late blight control by spraying potato leaves with double-stranded RNAs (dsRNA) that target the P. infestans genes essential for infection. First, we showed that the sporangia of P. infestans expressing green fluorescent protein (GFP) can take up invitro synthesized dsRNAs homologous to GFP directly from their surroundings, including leaves, which led to the reduced relative expression of GFP. We further demonstrate the potential of spray-induced gene silencing (SIGS) in controlling potato late blight disease by targeting developmentally important genes in P. infestans such as guanine-nucleotide binding protein β-subunit (PiGPB1), haustorial membrane protein (PiHmp1), cutinase (PiCut3), and endo-1,3(4)-β-glucanase (PiEndo3). Our results demonstrate that SIGS can potentially be used to mitigate potato late blight; however, the degree of disease control is dependent on the selection of the target genes.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Near Real Time Monitoring of Potato Late Blight Disease Severity using Field Based Hyperspectral Observation

Field spectroscopic study was performed using a hand-held Field Spectroradiometer to examine spectral variability between healthy and late blight disease infected potato canopy. The purpose was to select a suitable spectral feature in the visible-near infrared region for late blight disease initiation and severity during winter season. The spectral regions at which significant differences in bio-optical response was observed between healthy and diseased canopy include, 680-730nm (47.84%), 750-900nm (76.14%) and 860-1040nm (68.60%). Correlation study was carried out among different spectral variables, sensitive to PLB disease, and field measured PLB disease severity. Out of all the spectral variables, Red-Edge Normalised Difference Vegetation Index (NDVI705) and Disease Water Stress Index (DWSI) showed significant negative correlation (0.87 and 0.84 at 95% confidence level) and capable to predict the different level of potato late blight disease severity. A remote sensing based novel disease severity method was developed from the above mentioned spectral variables using multi-linear regression model and validated with very high correlation (R2 = 0.883). The scoring method developed could be a good proximal indicator for real-time field monitoring of potato late blight disease.

Potato late blight disease prediction using meteorological parameters in Northern Himalayas of India

Weather parameters play an important role in the spread of potato late blight of caused by Phytophthora infestans (Mont.) de Bary has historically been serious disease of potatoes through worldwide, including India. Due to spatial variation in prevailing weather conditions, its severity varies from region to region. Disease development process and the weather parameters are well understood and have been utilized for disease developing forecasting models and decision support system. Therefore, an experiment was conducted for two consecutive cropping seasons (2017 & 2018) to develop a forecasting model against late blight of potato using stepwise regression analysis for Northern Himalayas in India. Maximum and minimum temperature, relative humidity, rainfall and wind speed appeared to be most significant factors in the potato late blight disease development. The meteorological conditions conducive for the development of potato late blight disease were characterized. Maximum and minimum temperatures in the range of 15.0 – 28.0°C and 2.0 – 12.0°C were found favorable for potato blight disease. Similarly, relative humidity, rainfall and wind speed in the range of 85 - 95 per cent, 15.5 - 20.75 mm and 1.0 - 5.5 Km h-1, respectively, were conducive for potato late blight disease which are helpful in disease development.

Epidemiology of potato late blight disease and other major postharvest biotic stressesin Malawi

The epidemiology of Potato Foliar Late Blight (PFLB) disease (Phytophthora infestans) was quantified in major potato production areas of Malawi. Seed multiplication fields, tests clones and local farmers’ fields were sampled basing on Area Under Disease Progress Curve (AUDPC). The determined severity values were transformed into AUDPC coefficients characterizing rate of disease spreading across the crop. Results indicate minimum and maximum AUDPC values of 0 and 1050 respectively, with an average value of 233.57. The results show significant statistical differences in PLB disease across seed multiplication fields, test clones and local farmers’ fields. AUDPC values differed significantly (p < 0.001) among potato growing districts, as well as sources of seed (aeroponics, sandponics, and vendors). Post-harvest survey targeting potato tubers showed that tubers that were sampled from Mzimba district had the highest likelihood of being infected with Potato Tuber Late Blight (PTLB), followed by potatoes that were sampled from Lilongwe (coefficients, b= 1.89, t = 6.11, p-value<0.001) while the potatoes tubers that were sampled from Ntcheu did not vary in the severity with those that were sampled in Dedza. Susceptibility to potato PTLB among potato varieties were varied, with Rosita likelihood to PTLB disease, while there were no other significant differences to PTLB in the rest varieties (b=1.12, t=4.23, p-value<0.001). An extended study on bacterial wilt (PBW) revealed that disease was influenced by the district where the tubers were sampled (x2= 9.26, p-value < 0.001) while the type of variety sampled did not have any significant difference on PBW (x2= 3.59, p-value = 0.268). The presence of potato tuber moth which varied among the sampled districts, was not influenced by variety sampled. The paper has documented and quantified increasing epidemic spread of late blight disease and the consequent effect on sustainable potato production and clean seed systems in Malawi.

Smart Proactive Warning System for Early Prediction of Potato Late Blight Via Machine Learning

Precision agriculture is one of the applications which may use the Machine learning technology to maximize the crops productivity, optimize the quality of the crops, and minimize the negative environmental impact like crops diseases. Crop diseases are generally one of the most critical problems that threaten the worlds agriculture, causing large losses in agricultural production of about 25% per year. Some metrological data like relative humidity, temperature, wind speed, wind direction, and pressure play an essential role in the creation and spreading of late blight disease of potato. The proposed system aims to predict a potato late blight using a machine learning (ML) IoT based system trained on dataset collected from field sensors at crops environment through forecasting weather data from weather stations. The proposed system is designed based on Logistic regression and Neural Networks where model results show performance and accuracy improvements compared with the result of built in service created on Microsoft Azure cloud using the same data set.

The Assessment of Potato Late Blight Disease in Western Amhara Region, Ethiopia

Potato late blight disease (LBD) is the most important biotic constraints of potato production in Ethiopia. Hence, field assessment on 75 farmer fields in Banja, Guagusa Shikudad, Yilmana Densa, Farta and Lay Gaint districts was conducted during 2017 to assess the prevalence, incidence, severity and to assess the farmers perception about late blight disease and management methods and finally to draw possible recommendations for further LBD management in Western Amhara. All surveyed fields were found infected by late blight disease. Whereas, the incidence were varied from 30% at Lay Gaint to 100% at Banja and Guagusa Shikudad. Similarly, the mean severities also ranged from 30.56% in Lay Gaint to 69% in Banja. The district, altitude, soil type, previous crop, variety, plant density and cropping system were significantly associated with incidence and severity of LBD in logistic regression model. Based on the results obtained, LBD was found on all surveyed areas but the majority of farmers did not know the epidemiology, causative agent and proper management methods of the disease. Therefore, awareness should be created for potato producer farmers about the disease biology and its management opportunities. The disease management options should be demonstrated on these study areas.

Allelic variants of the NLR protein Rpi-chc1 differentially recognize members of the Phytophthora infestans PexRD12/31 effector superfamily through the leucine-rich repeat domain.

SUMMARYPhytophthora infestans is a pathogenic oomycete that causes the infamous potato late blight disease. Resistance (R) genes from diverse Solanum species encode intracellular receptors that trigger effective defense responses upon the recognition of cognate RXLR avirulence (Avr) effector proteins. To deploy these R genes in a durable fashion in agriculture, we need to understand the mechanism of effector recognition and the way the pathogen evades recognition. In this study, we cloned 16 allelic variants of the Rpi‐chc1 gene from Solanum chacoense and other Solanum species, and identified the cognate P. infestans RXLR effectors. These tools were used to study effector recognition and co‐evolution. Functional and non‐functional alleles of Rpi‐chc1 encode coiled‐coil nucleotide‐binding leucine‐rich repeat (CNL) proteins, being the first described representatives of the CNL16 family. These alleles have distinct patterns of RXLR effector recognition. While Rpi‐chc1.1 recognized multiple PexRD12 (Avrchc1.1) proteins, Rpi‐chc1.2 recognized multiple PexRD31 (Avrchc1.2) proteins, both belonging to the PexRD12/31 effector superfamily. Domain swaps between Rpi‐chc1.1 and Rpi‐chc1.2 revealed that overlapping subdomains in the leucine‐rich repeat (LRR) domain are responsible for the difference in effector recognition. This study showed that Rpi‐chc1.1 and Rpi‐chc1.2 evolved to recognize distinct members of the same PexRD12/31 effector family via the LRR domain. The biased distribution of polymorphisms suggests that exchange of LRRs during host–pathogen co‐evolution can lead to novel recognition specificities. These insights will guide future strategies to breed durable resistant varieties.

Studies on Intercropping Systems of Garlic and Green Onion to Potatoes and impact that on Growth, Yield, and Resistance Late Blight Disease

The study assessed the effect of intercropping Patterns on the performance of potato plants, i.e., vegetative growth, tuber quality and yield as well as potato late blight,Phytophthorainfestansdisease epidemiology. Trials were carried out under a greenhouse and open field in Moshtohor and Kaha, Qalyubia Governorate, Egypt, respectively during three successive winter seasons of 2016/2017, 2017/2018 and 20178/2019. Potatowas intercropped with garlic or onion at the ratios of 1:1; 2:1 and 3:1 plant population. These treatments were compared with fungicide (Radomil gold) foliar spray and unsprayed monoculture potato plant with respect to disease development and potato tuber yield and quality. The results prevailed that, all potato-garlic ratios exhibited superior performance when compared to the fungicide unsprayed treatment. Among the proportions, 1 potato with 1 garlic intercropped plots showed significantly low disease development and high tuber yield. Moreover, at 1:1 combination of garlic (or onion) to potato, the land equivalent ratio (LER) was greater than 1 and the monetary values were high at both testing sites. The study also demonstrated that fungicide treatment provided significant low disease development and higher potato tuber yield when compared to the untreated monoculture control treatment. The findings of this study suggested garlic as a potential intercropping plant for the management of potato late blight disease under Egyptian condition. In winter growing season, the extracts of garlic or onion plants reduced the disease severity of late blight. The effect of competition among the two different Allium species in potato intercropping and the economic viability of intercropping potato with garlic or onion compared to its sole cropping were studied under natural late blight infestation. Generally, the present study concludes that intercropping of potato with garlic and onion may affect yield and disease resistance, competition between the 2 species (Solanumtuberosum and Allium spp.), and economics of mixtures as compared to monoculture of the same species. Although Allium crops had lower yield in mixture but are more expensive in markets, solitary planting of them would not reach the profitable level gained with potato under our trials condition

Population structure of Phytophthora infestans in Turkey reveals expansion and spread of dominant clonal lineages and virulence

AbstractLate blight, caused by the oomycete Phytophthora infestans, is considered the most important and destructive disease of potato in Turkey. In this study, characterization of 367 isolates of P. infestans obtained from the potato‐growing areas of the country was carried out to evaluate the pathogen population structure over the 2017–2019 production seasons. The isolates were characterized by numerous features including mating type, in vitro mefenoxam sensitivity, simple‐sequence repeat (SSR) markers, and virulence against a set of potato differential lines. Most isolates were A2 mating type (353 isolates). Also, 68% of isolates were resistant to mefenoxam; the remainder were intermediate in their sensitivity and there were no sensitive isolates. SSR‐based genotypic analysis of P. infestans populations showed a low genetic diversity. The 13_A2 clonal lineage predominated with a frequency of 92.1%, followed by 34_A1 (3.3%) and 37_A2 (2.7%). Genotypes 34_A1 and 37_A2 were detected only in 2019. This is the first report of 34_A1 and 37_A2 clonal lineages causing late blight disease of potato in Turkey. The most abundant virulence type was one overcoming resistance genes R1, R2, R3, R4, R6, R7, R10, and R11. These results emphasized that the migration of individuals and the asexual generation of subclonal differences were the main factors driving the population structure of P. infestans in Turkey.

Efficacy of Some Botanical Extracts on the Control of Late Blight Disease in Experimental Potato Field

Late blight caused by Phytophthora infestans (Mont.) De Bary is the most devastating disease of potato. This study was carried out to evaluate the efficacy of ten botanical extracts against the late blight disease incidence and severity in experimental potato field at University of Rajshahi, Bangladesh during 2019-2020. Crude aqueous extract of leaves of Syzygium cumini, Psidium guajava, Eucalyptus globusus, Carica papaya and Lawsonia inermis; fruits of Terminalia bellirica, T. chebula and Piper nigrum; flower buds of Syzygium aromaticum and cloves of Allium sativum were used at 5% (w/v) concentration for evaluation. Out of ten botanicals, Syzygium cumini leaves extract was found most effective in controlling the late blight disease incidence and severity up to 66 DAS (days after sowing) and increased the potato yield by 71.29% compare to untreated control. The efficacy of Lawsonia inermis extract against late blight disease was found promising and increased the potato yield by 48.51%. Other four botanical extracts (Terminalia chebula, Piper nigrum, Syzygium aromaticum and Carica papaya) showed moderate efficacy against the incidence and severity of late blight disease, and increased 30% more potato yield compare to control. These results suggest that botanical extract of Syzygium cumini has a great potential as an alternative of chemical fungicides to control the late blight disease of potato in eco-friendly way.

Recent Advances in Potato Late Blight Disease Management Strategies

Potato is the world’s number one non-grain food commodity, with production reaching 325 million tons. Some inherent qualities give potato a competitive edge over the leading food crops. It is able to produce more protein and carbohydrates per unit area than cereals. Among all the crops grown worldwide, is known to suffer the greatest losses from disease attack. Among those diseases late blight and bacterial wilt are the most economical diseases which incurred 100% yield loss. The main Objective of this review was to understand very well the recent advances on potato late blight disease management up to gene for gene level and incorporate these recent molecular advances with the conventional one for mitigating the virulence spectrum of the pathogen. The population of P. infestans characterized using molecular markers has led to better understanding of pathogen at molecular level. Mitochondrial DNA haplotyping of P. infestans has revealed that mt Ia is displacing the other haplotypes globally at a faster rate.

Potato late blight disease detection using convolutional neural network

Potato late blight disease detection using convolutional neural network

Effect of Chemical Inducers of Systemic Acquired Resistance (SAR) for the Management of Late Blight Disease of Potato

Late blight of potato is one of the most devastating diseases with great economic importance. Among several disease management strategies, ISR (Induced systemic resistance) plays an important role in checking the disease spread. So, in the present study, nine different SAR chemical inducers viz. Phosphoric acid, Salicylic acid, Naphthalene acetic acid(NAA), Benzoic acid, Benzothiadiazole, Dichloro-iso nicotinic acid (INA) and Kinetin were evaluated at 0.05% (C1), 0.10% (C2) and 0.15% (C3) concentrations, whereas Calcium chloride and Ascorbic Acid at 3.5% (C1), 5.0% (C2), 6.5% (C3) and 1.5% (C1), 2.0% (C2), 2.5% (C3) respectively at three different concentrations each, along with positive and negative checks of standard fungicide metalaxyl 8+ macozeb 64 WP @0.25% and control(water) respectively by spraying them at 2-3 compound leaf stage of plants which were challenged by P. infestans inoculations five days later in pots to assess disease incidence and intensity which were recorded at weekly intervals of four stages (stage I-IV). It was found that the foliar spray with benzothiadiazole (BTH) @ 0.10 to 0.15% was best in delaying the appearance of first symptoms of the disease by 11 days followed by salicylic acid@ 0.10 to 0.15% and ascorbic acid @ 2.5% which delayed the symptom appearance by 9 days, whereas the standard fungicidal spray of metalaxyl 8 + mancozeb 64 WP at the recommended concentration of 0.25% delayed the symptom appearance by only 8 days when compared to water sprayed check. It was also found that on an average, BTH sprays completely arrested the late blight development (0% intensity) followed by salicylic acid, INA and ascorbic acid sprays exhibiting 0.46-0.74% mean blight intensity compared to 2.00 and 6.28 percent intensity recorded, respectively, on metalaxyl 8 + mancozeb 64 WP and water-sprayed plants one week after first appearance of disease in control pots (stage I). These treatments with chemical inducers showed an increase in the activity of peroxidases and polyphenol oxidases in the infected potato leaves as a result of SAR activity at all stages (stage I-IV). Average maximum peroxidase activity of 19.01-20.66 mg and polyphenol oxidase activity of 2.70-2.89 mg were recorded in the potato leaves during stage-I, sprayed with either BTH, benzoic acid, phosphoric acid or salicylic acid as compared to only (16.78 mg and 2.28 mg), (4.66 mg and 1.36 mg) recorded in (metalaxyl 8 + mancozeb 64 WP) and water-sprayed check respectively. The highest concentrations of all the test chemicals, in general, showed increased biochemical activity thereby yielding lesser blight intensity compared to their lower concentrations.

S-methyl Methanethiosulfonate: Promising Late Blight Inhibitor or Broad Range Toxin?

(1) Background: S-methyl methanethiosulfonate (MMTS), a sulfur containing volatile organic compound produced by plants and bacterial species, has recently been described to be an efficient anti-oomycete agent with promising perspectives for the control of the devastating potato late blight disease caused by Phytophthora infestans. However, earlier work raised questions regarding the putative toxicity of this compound. To assess the suitability of MMTS for late blight control in the field, the present study thus aimed at evaluating the effect of MMTS on a wide range of non-target organisms in comparison to P. infestans. (2) Methods: To this end, we exposed P. infestans, as well as different pathogenic and non-pathogenic fungi, bacteria, the nematode Caenorhabditis elegans as well as the plant Arabidopsis thaliana to MMTS treatment and evaluated their response by means of in vitro assays. (3) Results: Our results showed that fungi (both mycelium and spores) tolerated MMTS better than the oomycete P. infestans, but that the compound nevertheless exhibited non-negligible toxic effects on bacteria, nematodes and plants. (4) Conclusions: We discuss the mode of action of MMTS and conclude that even though this compound might be too toxic for chemical application in the field, its strong anti-oomycete activity could still be exploited when naturally released at the site of infection by plant-associated microbes inoculated as biocontrol agents.

Copper tolerant Trichoderma asperellum increases bio-efficacy of copper against Phytophthora infestans in dual combination

Present research was conducted to understand the characteristics of Trichoderma in the development of combination product involving a lower dose of Cu fungicide that showed promise in the effective management of Phytophthora infestans, the late blight pathogen of potato. Based on Cu tolerance activity, potential Trichoderma strains (viz., TCMS-36, SBIT-32 and TCMS-71) were selected. Electron microscopy (SEM and TEM) studies revealed that tolerant Trichoderma isolates (SBIT-32 and TCMS 36) accumulated Cu on the cell wall, while the sensitive isolate (TCMS 71) was repressed due to penetration of Cu through the cell wall. To elucidate Cu-tolerance, Cu-biosorption by living and dead mycelia of T. asperellum was estimated by atomic absorption spectrophotometer. Both sensitive and tolerant T. asperellum isolates accumulated Cu in their cells all through the observation period of 120 h, with considerable increase in the amount of Cu removed from the cell free supernatant from 24 to 120 h. Isolate TCMS-36 recorded maximum Cu accumulation (0.3506 mg/g) in living mycelia, while SBIT-32 recorded highest accumulation (0.2368 mg/g) in dead mycelia. Effectiveness of Cu tolerant T. asperellum was studied in combination with Cu fungicides; viz., COC (Blitox-50), COH (Kocide) in controlling late blight disease in the field. Among three modes of applications, viz., seed, foliar and seed+foliar, maximum delay in progress of the disease was recorded in seed+foliar application. Dual combination of COC@500 ppm and Trichoderma was found more effective than COC alone @1000 ppm in reducing disease severity. Cu tolerant Trichoderma strains could thus be developed as combination products with Cu-based fungicides for safe and effective management of late blight disease of potato.

Genetics of Pathogen–Host Interaction by the Example of Potato Late Blight Disease

This article is a review of modern conceptions concerning the interaction between a pathogen and a host plant at the molecular level. In particular, the basic principles of plant immunity and the mechanisms by which pathogens overcome this immunity are described. In this respect, special attention is paid to information about the interaction of the causative agent of late blight disease oomycete Phytophthora infestans (Mont.) de Bary with its host potato. This is due to the fact that late blight is the largest economically significant problem for modern potato farming. Despite the fact that the causative agent of late blight has been known to science for a long time, there are many unresolved issues related to the biology of this pathogen. Therefore, to create new potato varieties with high resistance to late blight, it is necessary to obtain new knowledge about the interaction of the polygenic plant resistance system with the determinants of pathogenicity of P. infestans.

Evaluation of fungicides for management of late blight (Phytophthora infestans) of potato

Late blight disease of potato, causal agent, Phytophthora infestans (Mont.) de Bary, is one of the serious diseases for potato production. Application of fungicides is an effective management option to control late blight. Field experiment was conducted during winter season of 2018 for evaluation of the efficacy of fungicides on late blight management and potato yields in research field of Prithu Technical College, Institute of Agriculture and Animal Science, Gadawa, Lamahi Dang, Nepal. Six fungicides i.e. Relaxyl (Metalaxyl 8% + Mancozeb 64 %), Antracol (Propineb 70 %), Sectin (Mancozeb 50% + Fenamidone 10%), Dithan M 45 (Mancozeb 75 %), Targon (Metalaxyl 35%), Bavistin (Carbendazim 50 %) and a nontreated control (NTC) were replicated three times in a randomized complete block design planted with late blight susceptible potato variety Cardinal. Fungicide application considerably reduced late blight progress, with a corresponding increase in tuber yield. The least disease severity (18.67%), least disease incidence (5.33%), least mean AUDPC (85.56) and highest tuber yield (9.49 kg/plot) were recorded on application of Sectin @ 2 g/L. The disease incidence and AUDPC value was negatively corelated with the tuber yield. The result revealed that the fungicide Sectin was most effective in controlling late blight disease of potato and to increase tuber yield.