The potato (
Solanum tuberosum L.), a member of the Solanaceae family, is a crucial global crop due to its nutritional content, economic significance and adaptability to diverse agricultural environments. It ranks as the fourth-largest food crop worldwide, following maize, wheat and rice and plays a significant role in food security by providing calories and essential nutrients. China leads global potato production, followed by Russia and India. In India, potato cultivation spans 2.32 million hectares, yielding 56.17 million tonnes. Uttar Pradesh ranks highest in production, with 19.17 million tonnes, followed by West Bengal, Bihar, Gujarat and Madhya Pradesh
(Ram et al., 2024). Potatoes are high in carbohydrates, primarily as starch and contain important nutrients like vitamin C, potassium and dietary fiber
(Camire et al., 2009). As a staple, potatoes are widely consumed, with adults averaging 300-800 grams daily (
De Haan et al., 2019). The crop’s adaptability to different climates and soils supports its global cultivation, with thousands of genetically diverse varieties suited to specific environments and culinary uses.
Late blight, caused by the oomycete
Phytophthora infestans (Mont.) de Bary, is a major disease affecting potatoes and tomatoes worldwide
(Son et al., 2008). This pathogen significantly threatens potato production, causing severe yield losses and economic damage (Table 1), particularly in regions like Northern Europe, including Ireland, where it triggered the Irish Potato Famine (1843-1845), resulting in mass starvation and emigration
(Elansky et al., 2001). Recognized as the most damaging disease for potatoes (
Agrios, 2005), late blight continues to impact production systems globally (
Madden, 1983). Regional losses due to late blight are particularly severe in Sub-Saharan Africa (44%), followed by Latin America (36%), the Caribbean (36%), Southeast Asia (35%), Southwest Asia (19%) and the Middle East and North Africa (9%)
(Erwin et al., 1983; Singh and Shekhawat, 1999;
Singh and Bhat, 2003;
Fry, 2008;
Lozoya-Saldana, 2011). The disease affects yield-related traits such as tuber yield and can lead to total crop loss in severe cases (
Mercure, 1998;
Pandit et al., 2020).
In India, late blight results in an average potato yield loss of 10-15%
(Lal et al., 2016). In Karnataka, regions such as Hassan and Belur experience disease severity levels ranging from 3% to 100%, with an average severity of 54.8%. For instance, Belur recorded a 70% severity rate in 2013. Punjab has also faced significant yield reductions due to late blight. Similarly, high humidity in Uttar Pradesh exacerbates the disease, adversely affecting both yield and quality. In Maharashtra, late blight is a major production challenge, with reports suggesting considerable yield losses. Overall, productivity and yield decline from late blight vary between 25% and 85%, depending on the susceptibility of potato cultivars
(Kumar et al., 2003).
Despite advancements in agricultural practices, late blight continues to cause substantial economic losses through reduced yields and higher production costs related to disease management. Breeding programs aim to enhance yield, disease resistance and nutritional quality, with biotechnology aiding the development of potato varieties with improved traits. This genetic diversity is crucial for building crop resilience against pests, diseases and changing climates. Successful potato cultivation requires suitable soil preparation, planting, irrigation, pest and disease management and harvesting. Potatoes thrive in loose, well-drained soils rich in organic matter. Crop rotation and certified, disease-free seed potatoes are vital in preventing soil-borne diseases
(Tiwari et al., 2021). Integrated disease management (IDM), incorporating cultural, biological and chemical control measures, along with resistant varieties, offers effective and environmentally safe disease control (
Tsedaley, 2014). This review intends to provide an in-depth look at late blight, examining pathogen biology, disease dynamics and contemporary management approaches.
Symptomatology
Late blight of potato, caused by
Phytophthora infestans, manifests through distinct symptoms on leaves, stems and tubers showed in Fig 1 to 3. Symptoms include pale green to dark brown water-soaked lesions, primarily near the tips and margins of leaves, which quickly expand into large, brown to purplish-black necrotic spots. These lesions are often the first visible signs of infection (
Fry, 2008). Under favorable conditions, the disease spreads rapidly; leading to extensive blighting where entire leaves and even plants can collapse and die, resembling frost damage (
Grunwald and Flier, 2005). In humid environments, a white, downy growth appears on the underside of infected leaves, especially at the edges of necrotic lesions, indicating sporulation (
Fry and Goodwin, 1997). Infected stems develop dark brown to black elongated lesions, leading to girdling and plant death in severe cases
(Haverkort et al., 2009). Lesions on stems are less common than on leaves but are a serious indicator of disease spread. Infected tubers show irregular, sunken lesions that are brown to purple (
Fry, 2008). Cutting open an infected tuber reveals reddish-brown to dark brown granular rot extending inward from the skin (
Grunwald and Flier, 2005). These infected tubers are usually hard, dry and discolored, contrasting sharply with healthy tissue and may be further attacked by bacteria causing soft rot, leading to rotting in the field and storage.
Host range
P.
infestans is well known for causing severe damage to a variety of crops, particularly within the Solanaceae family. Its host range is relatively narrow, with a primary focus on potatoes (
Solanum tuberosum) and tomatoes (
Solanum lycopersicum), where it is the primary causal agent of late blight (
Fry and Goodwin, 1997;
Nowicki et al., 2012). However, under certain environmental conditions,
P.
infestans can also infect other Solanaceous plants, including brinjal (eggplant) and chili peppers, leading to additional crop losses.
Etiology and biology of phytophthora infestans
P.
infestans, the pathogen responsible for late blight, originates from Central Mexico (
Zimnoch-Guzowska et al., 2003). The mycelium of
P.
infestans is endophytic, consisting of hyaline, highly branched coenocytic hyphae that are intercellular, with single or double club-shaped haustoria or haustoroid hyphae. The sporangiophores are thick-walled, with cross partitions and the side branches show bulbous enlargements at intervals, indicating where sporangia are attached. The sporangia are multinucleate, thin-walled, hyaline, oval, pear, or lemon-shaped, with a distinct papilla at the apex. Zoospores are biflagellate, motile spores released directly from the sporangium through the papilla. Low temperatures favor zoospore formation, while higher temperatures favor germination of the sporangium by germ tubes. The pathogen’s frequent emergence of new pathogenic types due to its variability creates challenges in the field, as does the sectoring of fungal colonies often observed in laboratory settings. Early studies by
Giddings and Berg (1919) and
Berg (1926) were instrumental in detecting variations in
P.
infestans populations.
Taxonomy and life cycle
Phytophthora infestans belongs to the class Oomycetes, a group of fungus-like organisms known for their complex life cycles (Fig 4), which include both asexual and sexual reproduction (
Judelson, 1997). Asexual reproduction in
P.
infestans involves the production of sporangia, which release motile zoospores under favorable conditions. These zoospores are capable of swimming, encysting and subsequently germinating to infect host tissue. Under suitable environmental conditions, the asexual life cycle can be repeated multiple times within a week, leading to rapid disease proliferation
(Nowicki et al., 2012). The survival of sporangia for subsequent infections is primarily confined to host tissues, with limited knowledge regarding their
viability in soil or other dead organic matters. The predominance of the asexual life cycle results in multiple disease cycles within a single growing season
(Drenth et al., 1995). Sexual reproduction occurs when opposite mating types (A1 and A2) come into contact, leading to the formation of oospores. These oospores can survive in soil and plant debris for extended periods, serving as a primary inoculum source in subsequent growing seasons (
Judelson, 1997).
Disease cycle and epidemiology
The infection process of
P.
infestans begins when sporangia or zoospores land on the surface of potato foliage or tubers. Under favorable environmental conditions, these spores germinate and penetrate the host tissue through stomata or wounds. Once inside the plant, the pathogen colonizes the intercellular spaces and produces haustoria, specialized structures that extract nutrients from host cells. This leads to tissue necrosis and the characteristic symptoms of late blight, including water-soaked lesions on leaves, stems and tubers (
Birch and Whisson, 2001).
In regions where field soil temperatures remain below 30
oC,
P.
infestans can persist as dormant mycelium in tubers left in the field. In areas where seed tubers are stored at low temperatures, the mycelium in these tubers acts as the primary inoculum source for the next growing season. The pathogen thrives on live host tissue, including seed tubers, cull piles, volunteer potatoes and other Solanaceous plants, as well as in soil
(Shinners et al., 2003; Kirk et al., 2013). P.
infestans demonstrates high adaptability and can spread rapidly under favorable environmental conditions. Primary dissemination occurs through wind-borne sporangia, rain splash and human activities, such as the transport of infected plant material (
Fry, 2008). Secondary infection cycles are initiated when sporangia from infected plants spread to healthy plants, perpetuating the epidemic. The development of late blight is heavily influenced by environmental factors. High humidity (above 90% RH), rainfall and temperatures between 15-25°C create optimal conditions for sporangia production and zoospore release. Prolonged leaf wetness is crucial for infection, as it allows zoospores to swim and encyst on leaf surfaces (
Harrison, 1992). The level of tuber infection is closely related to rainfall during the fungus’s sporulation on foliage. Heavy and frequent rains, particularly when 50% of the foliage is infected, result in maximum infection of underground tubers
(Arora et al., 1987).
Host-pathogen interactions
Potato plants are susceptible to late blight throughout their growth stages, with the highest risk occurring during the tuber bulking period. Symptoms include water-soaked lesions that rapidly expand, leading to extensive tissue decay. Infected tubers display a characteristic brown, granular rot that can penetrate deep into the tissue, rendering them unmarketable (
Crosier, 1934). The interaction between
P.
infestans and its host involves a complex exchange of molecular signals. The pathogen secretes various effectors that manipulate host cellular processes, facilitating infection and suppressing immune responses
(Bos et al., 2009). These effectors are delivered into host cells
via specialized infection structures known as haustoria. In response, the host plant has evolved a range of defense mechanisms to detect and counteract pathogen invasion. These defenses include pathogen recognition receptors (PRRs) that detect conserved microbial patterns, triggering the activation of basal defense responses
(Kamoun et al., 1999). Additionally, the host may possess resistance (R) genes that recognize specific pathogen effectors, leading to a more robust defense response known as effector-triggered immunity (ETI) (
Jones and Dangl, 2006). However, the high genetic variability of
P.
infestans allows it to quickly adapt, overcoming host resistance and leading to the emergence of new, more virulent strains.
Monitoring and management strategies
Machine learning tools for early prediction of potato late blight
Early prediction of potato late blight plays a critical role in supporting precision agriculture. Weather forecasting and warning systems leverage meteorological parameters, such as relative humidity, temperature, wind direction and wind speed, to predict disease onset. By analyzing these variables, the system can effectively forecast late blight in potatoes. Machine learning models, incorporating algorithms like logistic regression and neural networks, have been developed to predict this disease (
Mohammad, 2021). The system compares the performance of these algorithms on the same dataset to identify the most accurate and suitable model.
Convolutional neural network (CNN)
Continuous monitoring of plant diseases, particularly identifying infected leaves, poses a challenge. Convolutional Neural Networks (CNNs) address this by classifying potato diseases more efficiently through image-based phenotyping, which reduces the computational time required for processing learnable parameters. To further enhance the CNN model, a meta-heuristic algorithm known as the Whale Optimization Algorithm (WOA) is used to optimize its hyperparameters (
Kiran Pandiri et al., 2022). The optimized CNN, named POT-Net, classifies potato diseases with high accuracy. Its performance is evaluated using metrics such as precision, recall, F1-score and accuracy. POT-Net achieves a 99.12% accuracy rate, outperforming pre-trained deep learning models and other optimized algorithms, thus surpassing state-of-the-art models.
Cultural practices
Cultural methods are essential for managing late blight, with key strategies including crop rotation, the elimination of volunteer plants and maintaining good field sanitation to reduce the primary sources of infection. To minimize leaf wetness and lower the risk of infection, it is advisable to avoid overhead or nighttime irrigation and ensure adequate air circulation
(Draper et al., 1994). Additionally, using disease-free seed potatoes and maintaining proper plant spacing can help prevent the spread of the disease
(Stevenson et al., 2007). Effective management also involves removing cull piles and volunteer potatoes, employing proper harvesting and storage techniques and applying fungicides when necessary
(Davis et al., 2009). The researchers
Bodker et al., 2006 and
Hannukkala et al., 2007 demonstrate that crop rotations of three or more years between potato crops significantly reduce the risk of soil-borne infections by
Phytophthora infestans.
Chemical control
Fungicides play a crucial role in managing late blight, commonly used protectant fungicides include chlorothalonil and mancozeb, while systemic fungicides such as metalaxyl are also frequently applied (Table 2). However, the overuse of metalaxyl-based fungicides has led to the development of resistance globally, including in India
(Arora et al., 2014). This resistance has necessitated the adoption of integrated pest management (IPM) strategies, which involve rotating fungicides with different modes of action and combining chemical treatments with other methods to reduce the risk of resistance development
(Gisi et al., 2011).
Biological control
Biological control offers a promising alternative to chemical fungicides. Various antagonistic microorganisms, such as
Trichoderma spp. and
Bacillus spp., have shown potential in suppressing
P.
infestans. These biological agents can inhibit the pathogen through competition, antibiosis and induction of host resistance. For instance,
Bacillus subtilis B5 has been tested using the dual culture method and found effective in inhibiting the growth of
P.
infestans (
Ajay and Sunaina, 2005). Other bioagents, including
Pseudomonas fluorescens,
Pseudomonas sp.,
Aspergillus flavus,
A.
niger,
Penicillium sp.,
Trichoderma virens and
T.
harzianum, have also been reported to inhibit
P.
infestans (Lal et al., 2013). Ongoing research aims to develop effective biocontrol formulations that can be integrated into existing management programs
(Whipps, 2001).
Genetic resistance
Breeding for resistance is a sustainable approach to managing late blight. Several potato varieties, such as Kufri Anand, K. Arun, K. Badshah, K. Pukhraj, K. Satluj, K. Sadabahar, K. Jawahar, K. Chipsona-I, K. Chipsona-II, K. Girdhari and K. Kiran, have demonstrated moderate to high resistance against late blight, as developed by the Central Potato Research Institute (CPRI) in Shimla, India. The incorporation of R genes from wild potato relatives has led to the development of resistant cultivars. However, the rapid evolution of
P.
infestans often overcomes these resistances, necessitating continuous breeding efforts to introduce new R genes and combine multiple genes to achieve durable resistance (
Bradshaw and Bonierbale, 2010). Researchers have documented variations in resistance among different potato varieties
(Njualem et al., 2001). Additionally, biotechnology is being utilized to develop late blight resistance, although genetically modified plants for disease resistance are not acceptable for organic production
(Shapiro et al., 1998).
Current research and future directions
Genomics and biotechnology
Advances in genomics and biotechnology are enhancing our understanding of
P.
infestans and its interactions with potato hosts. The whole genome sequencing of
P.
infestans has provided insights into its genetic diversity and pathogenicity mechanisms
(Haas et al., 2009). Techniques like CRISPR/Cas9 are being explored to develop resistant potato varieties by precisely editing R genes and studying pathogen virulence factors (
Vleeshouwers and Oliver, 2014).
Epidemiological modeling
Improved epidemiological models are aiding in the prediction of late blight outbreaks and informing timely management interventions. A disease forecasting model anticipates the occurrence or variations in the severity of one or more diseases by analyzing data related to weather, crops, pathogens, or a combination of these factors. Over time, several forecasting models have been designed and applied worldwide to predict late blight in potatoes
(Singh et al., 2013). These models incorporate weather data, pathogen biology and host resistance information to provide accurate risk assessments. Decision support systems based on these models can help farmers optimize fungicide applications and reduce unnecessary treatments
(Skelsey et al., 2009). Singh et al., (2000) developed the computerized forecasting model ‘JHULSACAST’ for western Uttar Pradesh, which has been validated and can accurately predict late blight in the region. This model is like the BLITECAST model developed by
Krause et al., 1975 but is designed for forecasting the initial appearance of late blight. JHULSACAST has also been calibrated for other regions in India, including the Tarai region of Uttarakhand and the plains of West Bengal
(Pundhir et al., 2014; Chakraborty et al., 2014). Based on JHULSACAST, a Decision Support System (DSS) has been developed, which includes three components: (i) prediction of the first appearance of the disease, (ii) decision rules for need-based fungicide application and (iii) a yield loss assessment model.
Sustainable practices
Sustainable late blight management requires an integrated approach that combines cultural, biological and chemical controls. Emphasizing reduced reliance on chemical fungicides and promoting environmentally friendly practices is crucial for long-term disease control. Developing resilient agricultural systems and fostering collaboration among researchers, extension services and farmers will be essential to achieving sustainable management of late blight
(Kirk et al., 2013).
