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Review

Progress in Research on Prevention and Control of Crop Fungal Diseases in the Context of Climate Change

by
Jien Zhou
1,2,3,†,
Xueyan Zhang
1,2,†,
Zheng Qu
1,
Chenchen Zhang
1,
Feng Wang
1,2,
Tongguo Gao
4,
Yanpo Yao
1,* and
Junfeng Liang
1,*
1
Agro-Environmental Protection Institute, Ministry of Agriculture and Rural Affairs, Tianjin 300191, China
2
Dali Comprehensive Experimental Station of Environmental Protection Research and Monitoring Institute, Ministry of Agriculture and Rural Affairs (Dali Original Seed Farm), Dali 671004, China
3
College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830052, China
4
College of Life Sciences, Hebei Agricultural University, Baoding 071001, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agriculture 2024, 14(7), 1108; https://doi.org/10.3390/agriculture14071108
Submission received: 3 June 2024 / Revised: 28 June 2024 / Accepted: 2 July 2024 / Published: 9 July 2024
(This article belongs to the Special Issue Strategies to Improve the Security and Nutritional Quality of Crop Species)
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Abstract

:
With an advancement in global climate change, the frequency of extreme climatic events, such as high temperature, drought, and flooding, has increased. Meanwhile, outbreaks of crop fungal diseases are becoming more frequent and serious, and crop growth and food production are seriously threatened. This article focuses on the climate change-related aggravation of crop fungal diseases; summarizes the progress in research on the impact of climate change on soil-borne fungal diseases, air-borne fungal diseases, and seed-borne fungal diseases; and discusses the conventional methods for diagnosing crop fungal diseases. On the basis of comparative analysis, the concept of ecological control is proposed; ecological control can maintain the dynamic balance of crop–biology–soil, provide a good environment for the healthy growth of crops, and provide a new fungal disease control method in the context of climate change.

1. Introduction

By 2050, the world’s population will exceed 9.7 billion, and human demand for food will continue to grow. However, crop yields globally have suffered severe declines due to disease, with 70–80% of crop diseases being caused by fungi [1]. There are approximately 1.5 million fungal species globally, of which Fusarium alone causes wilt and root rot in more than 100 crops [2], such as tomato wilt [3], corn rusts [4], and wheat fusarium head blight [5]. Indeed, most crops are susceptible to fungal diseases, with rice blast [6], wheat common smut, and wheat stem rust [7] causing 10–35% and 15–20% yield losses in rice [8] and wheat [9]. Although fungal diseases already pose a serious threat to global food security [10], the advancement of climate change has deepened this threat, highlighting the urgency of the challenge that this poses for humans.
It is widely recognized that climate change has the potential to decrease the productivity of food crops [11,12,13,14]. With global average temperatures having risen by 1.5 °C since the industrial revolution. The model predicts that an increase in temperature of 1.6 °C–3 °C will result in an 18–32% reduction in potato yields [15], which is particularly concerning given that the median global temperature is projected to rise by 2.6 °C–3.1 °C in 2100 [16,17]. As such, the reductions in crop yields seen to date may become far more severe in the future. In addition, climate change stimulates the growth of fungi that are pathogenic to crops and increases the incidence of fungal diseases. Higher temperatures would increase the relative abundance of most fungal pathogens globally [1], and fungal pathogens are more aggressive at higher temperatures (Figure 1) [18]. Flooding also promotes the spread of pathogenic fungi through soil runoff. For example, it has been shown that Colletotrichum rapidly infects and causes disease after reaching onion cultivations through rainfall washout transmission [19]. In addition, an increase in relative humidity due to flooding can trigger outbreaks of leaf spot or other fungal diseases in winter wheat [20]. It has also been reported that under drought and salt stress conditions, the rate of infection of broad bean root rot increases to 25–100% [21].
Overall, in the context of global climate change, fungal diseases of crops become established more rapidly, spread over a wider area, and are more damaging [18]. Moreover, the chemical pesticides that are currently most commonly used are no longer adequate because they damage plants and lead to resistance of pathogenic fungi and environmental destruction [22,23]. This background has prompted researchers to rethink microbe–crop–soil interactions as a whole to achieve ecological prevention and control of fungal diseases. This article focuses on the climate change-related aggravation of crop fungal diseases; summarizes the progress of research on the impact of climate change on soil-borne, air-borne, and seed-borne fungal diseases; discusses the methods for diagnosing crop fungal diseases; and proposes ecological prevention and control methods for maintaining crop health and preventing and controlling crop fungal diseases based on comparative analyses of such approaches.

2. Climate Change Exacerbates Crop Fungal Diseases

Increased frequency of extreme weather events due to climate change, such as droughts, floods, and high temperatures, has exacerbated the prevalence of crop fungal diseases at an alarming rate. This has in turn affected the growth cycle, yield, and quality of crops [24,25].

2.1. Drought Exacerbates Crop Fungal Diseases

Drought stress reduces crop fine roots and soil microbial diversity, allowing disease-causing fungi to infect crops more readily [26]. Studies have shown that drought exacerbates faba bean wilt [21], chickpea root rot [27], rice blast [28], and grapevine disease [29]. The lack of attention and efforts to prevent and control soil-borne pathogens in arid areas makes them more likely to cause significant damage [30]. It was reported that an annual drought in May–June significantly increases the incidence of rust in winter wheat in Poland [31]. Moreover, drought stress-induced soil salinization has been reported to increase the susceptibility of crops to pathogens and promote the spread of fungal crop diseases [32]. The interaction between crop salt stress and pathogen infection depends on the type of pathogen and the host crop species. For example, onions exposed to salt stress conditions suffer from more severe infestation with Fusarium oxysporum than those not exposed to salt stress [33,34]. Moreover, increased salinity of irrigation water significantly exacerbated cucumber damping-off disease caused by Pythium aphanidermatum [35].

2.2. Flooding and High Humidity Exacerbates Crop Fungal Diseases

Extreme precipitation can lead to frequent flooding and an increase in pathogenic fungi [31]. For example, precipitation or soil runoff can promote the spread of disease via spores of pathogenic fungi in the soil and in the air [36]. Prolonged rainfall makes it easier for Fusarium to attack wheat, which is more susceptible to tan spot disease [37]. Indeed, dramatic increases in the levels of pathogens such as Phytophthora, Fusarium, and Pythium have been reported after flooding [38]. In addition, the transport and agglomeration of fungal spores of Epicoccum tritici were found to be promoted by water condensation and evaporation [39]. Moreover, sugarcane is known to be more susceptible to false floral smut under conditions of high precipitation or high humidity [40], while the incidence of cashew leaf blight was shown to increase by 2% for every 1 mm increase in precipitation [41]. The number of spots in chickpea was also found to increase with increasing rainfall [42], while the incidence and severity of quinoa downy mildew increased under flooded conditions [43]. Finally, it was found that the likelihood of rice leaf blight and brown spot occurring simultaneously increases with increasing soil water content [44].

2.3. High Temperatures Exacerbate Crop Fungal Diseases

High temperatures are among the most direct manifestations of climate change, and prolonged high temperatures can increase the extent and severity of crop diseases [45]. For example, elevated temperatures can lead to pathogen spore germination, crop root damage, and an increased incidence of disease in susceptible crops. For example, the germination time of Botryosphaeria as the causative agent of grapevine trunk disease was found to be shorter at elevated temperatures [46], exacerbating this disease [47]. High temperatures were also shown to increase the incidence of root rot in celery, mainly due to the reduced expression of Fusarium resistance [48]. Soybean was also reported to suffer a higher incidence of Fusarium solani-induced root diseases at 30 °C [49], and soybean is more susceptible to sudden death syndrome at 37 °C, indicating that disease transmission is sensitive to temperature. Temperature changes also cause spot growth, increased infection efficiency, and spore formation of potato late blight, along with increases in infection efficiency, spot growth rate, and spore formation occurring under fluctuating temperature conditions compared with the rates at a constant temperature [50]. Moreover, elevated storage temperature also exacerbates crop fungal diseases, with a significant growth in the rice mold population being identified after 16 weeks of storage at 40 °C [51], showing incidence rates as high as 96.5%–99.1%. Moreover, while no decay occurred in carrots at a storage temperature of 10 °C, decay was greatest when the temperature rose to 35 °C [52]. It has also been found that increasing storage temperature from 2 °C to 25 °C increased the risk of infection of nectarines with brown rot by more than 60-fold [53] (Table 1).

3. Impact of Climate Change on Crop Fungal Diseases with Different Routes of Transmission

Crop fungal diseases are mainly categorized into soil-borne fungal diseases, air-borne fungal diseases, and seed-borne fungal diseases according to the transmission route. Climate change can alter the sites of infestation, disease levels, and mechanisms by which fungi cause damage via different transmission routes.

3.1. Soil-Borne Fungal Diseases

Soil-borne fungal diseases occur when fungi residing in the soil alongside crop remnants invade crop roots or stems under favorable conditions. These diseases hinder root functionality and the absorption of water and nutrients, resulting in stunted growth and decreased crop yields [54]. Especially in cases where there are continuous cropping and soil degradation, outbreaks of soil-borne diseases can frequently occur [55]. For example, potato late blight causes annual losses of approximately EUR 6.1 billion globally [56], and potatoes are more susceptible to extreme summer temperatures and drought [57]. The ratio of mild evapotranspiration to precipitation limits crop diversity, and extreme summer temperatures and drought make it easier for pathogens to attack crops, with some soil-borne pathogens, such as Pythium spp., Phytophthora spp., Fusarium spp., and Mycosphaerella spp., leading to crop yield reductions of 50–75% [58]. Climate change causes soil acidification, which alters the physicochemical properties and microbial communities of soil, promoting the accumulation of pathogens and exacerbating soil-borne diseases [59]. Acidic soils are in turn associated with the greatest incidence of Fusarium-induced root rot diseases of soybeans. Extreme climate conditions predispose crops to injury, and such vulnerable crops are more susceptible to disease. It has been reported that temperatures above 30 °C trigger oxidative stress in grains, which directly damages enzymes and tissues [60], and fungi such as Aspergillus and Fusarium oxysporum often parasitize and proliferate through sites of damage in crops [61]. There is increasing evidence to suggest that soil-borne diseases are not solely caused by individual species, but rather by pathogenic complexes [62,63,64,65], and the complexity of soil-borne pathogen–environment interactions is highlighted by the existence of multifaceted and contrasting interactions, such as those with temperature and humidity [66]. This complexity is further aggravated by the unpredictable and fluctuating proportions of diverse pathogens, which vary significantly across seasons and regions [67].

3.2. Air-Borne Fungal Diseases

Air-borne fungal diseases involve the spread of crop pathogens via spores aided by air currents to cause crop disease epidemics and associated damage. Pathogenic fungi, such as Cladosporium, Penicillium, and Aspergillus (including the species Aspergillus fumigatus), are present in the air [68] and cause air-borne fungal diseases including gray mold, downy mildew, powdery mildew, and early blight [69]. Individuals or groups of pathogens that are rapidly transmitted through the air can cause a wide range of diseases, intense outbreaks, and serious disasters. The spread of yellow rust to Australia in 1978 is an example of the spread of an air-borne disease [70], where the original rust fungus originated in Europe [71,72]. Another case of this kind involved Australian wheat stem rust, which occurred for the first time in Ethiopia in the mid-1980s, followed by its gradual emergence in the Middle East and the Indian subcontinent [73,74]. Increased air-borne sporulation is driven by higher temperatures and increased humidity. Studies have shown that temperature is the most important variable for the spread of Alternaria spores in Spain [75]. Meanwhile, it has been reported that warm climatic conditions in France promote the rapid growth of Cladosporium fungal spores [76]. Spores are transported over long distances by diffusion into the surrounding area through droplets or air [77]. Cucurbit downy mildew caused by the oomycete Cuban pseudofungus spreads rapidly [78], and it has been shown that relative humidity above 90% and a temperature between 15 °C and 20 °C are the optimal conditions for downy mildew [79], leading to yield losses of up to 80% in European cucurbits [78,80]. Another example of an air-borne fungal disease is black spot caused by Venturia inaequalis, which is an important disease of apples worldwide [81] and can cause 70% yield loss [81,82,83]. Meanwhile, early blight caused by Alternaria solani is a common disease of potato [84,85] that causes great damage under high-temperature conditions [86,87]. It has been reported that early blight is likely to become more severe in European potato-cultivating areas in the future [88].

3.3. Seed-Borne Fungal Diseases

Seed-borne fungal diseases are those in which the seed produced by a crop carries a pathogenic fungal propagule that develops at a certain stage of growth after the seed has been sown when suitable climatic conditions prevail. The fungal pathogens can be present on the outside or inside of the seed and may cause seed septoria, rot, and necrosis as well as impairing seedling growth [89]. When a crop pathogenic fungus binds to the seed, it may cause significant economic losses [90]. For example, when healthy wheat seeds are infested with Tilletia caries, even when sown into uninfested soil, the seed germinates and the latent pathogen invades the wheat spike as it spreads through the wheat seed [56], resulting in reduced seed quality and toxic metabolite production [91]. Aspergillus flavus, the seed-borne fungal pathogen of mungbean, is a toxic pathogenic fungus whose pathogenicity is primarily related to aflatoxin. It has been found that the rate of A. flavus colonization and the aflatoxin concentration in peanuts increase at temperatures close to 35 °C [92]. Increased storage temperature and humidity can lead to seed ulceration. High relative humidity during storage conditions can lead to pathogenic fungal growth, which can negatively impact the germination and growth of rice seeds [93]. Meanwhile, with increasing water content or storage temperature of soybean seeds, pathogenic fungi produce chemicals that accelerate seed deterioration [94] (Table 2).

4. Control of Fungal Diseases of Crops

The precise diagnosis of fungal diseases is a prerequisite for improving the effectiveness of prevention and control of such diseases in crops. Different crop diseases, different transmission routes, and diseases at different reproductive periods require the adoption of highly sensitive detection technologies and means. Disease prevention and control are currently divided into disease-resistant breeding, agronomic measures, chemical control, biological control, and ecological control.

4.1. Disease Detection

4.1.1. Methods for Diagnosing Fungal Diseases of Crops

The timely detection of crop diseases and their reliable diagnosis can make a major contribution to maintaining total food production globally [95]. Methods for diagnosing fungal diseases in crops can be divided into two categories: traditional and modern detection methods. Traditional detection methods mainly rely on morphological, microbiological, and biochemical identification, with fungal pathogens being detected by visual inspection methods and culture methods. The results of visual inspections are greatly influenced by the knowledge and experience of the inspectors, and have limited accuracy in the on-site diagnosis of fungal pathogens of crops [96]. Meanwhile, the culture method is time-consuming, with 3–5 days usually being required to cultivate the fungus [97]. In conclusion, traditional detection methods are time-consuming, ineffective, and unsuitable when efficient and rapid detection is required. Meanwhile, modern detection methods can be subdivided into direct and indirect detection methods, which are the main current methods for diagnosing fungal diseases.

Direct Detection Methods

Direct detection methods can be categorized into immunological methods and polymerase chain reaction (PCR) methods. The principle of immunological methods is based on the binding of antigen and antibody, and these methods include the immunodiffusion test, enzyme-linked immunosorbent assay, radioimmunosorbent assay (RISA), and dot immunobinding assay (DIBA) [98]. In terms of their advantages over traditional culture methods, immunological methods have a short detection time, but they have the disadvantages of low detection sensitivity and accuracy, as well as interference by contaminants. Meanwhile, PCR methods can detect specific target nucleic acids of the target pathogens and improve the specificity, sensitivity, and speed of detection [99]. However, they have the disadvantages of a lack of standardization, the need for additional preparation of samples, the difficulty of on-site operation, the need for special equipment, and the high cost of detection [100]. Overall, in the context of climate change, the above two methods are not suitable for diagnosing fungal pathogens in crops.

Indirect Detection Methods

Indirect detection methods identify crop diseases not by directly identifying the pathogen but by detecting the physiological response of the crop to the pathogen. The main indirect detection techniques include spectroscopy, biosensor detection, gas chromatography and mass spectrometry detection, and imaging techniques.
(1)
Spectroscopy. Spectroscopy is used to assess the health of a crop by irradiating light of a specific wavelength onto the crop tissue and measuring the intensity of the light wavelengths reflected back. Examples of types of spectroscopy include fluorescence spectroscopy, visible spectroscopy, infrared spectroscopy, and nuclear magnetic resonance spectroscopy. Near-infrared spectroscopy can detect maize spot disease and olive leaf spot [101,102]. However, spectroscopic methods cannot detect diseases before they develop in crops and cannot detect multiple diseases occurring at the same time.
(2)
Biosensors. A sensor is an analytical device that converts chemical, physical, or biological information into a useful analytical signal. A biosensor is “an integrated receptor–transducer device capable of providing selective quantitative or semiquantitative analytical information using biometric elements” [103]. In recent years, biosensors have attracted much attention due to their good results in detecting, classifying, diagnosing, and quantifying crop diseases. Biosensors can be categorized into optical biosensors, volatile biosensors, electrochemical biosensors, and mass-sensitive biosensors. Despite the ability of biosensors to rapidly and accurately detect disease-causing fungal pathogens, only a few devices are commercially available for detecting crop fungal pathogens in crops [104].
(3)
Gas chromatography coupled with mass spectrometry (GC–MS). GC–MS is a technique for analyzing volatiles produced by fungal infections in crops [105]. It has the advantages of not destroying the crop and enabling continuous monitoring for a long time [106], but it has the disadvantages of environmental factors such as humidity potentially interfering with the sensor readings [107] and the need to collect volatile organic compound samples prior to the GC–MS analysis, which limits its application in the field.
(4)
Imaging technology. Imaging technologies include thermal, hyperspectral, and red–green–blue (RGB) and fluorescence imaging, coupled with unmanned aerial vehicles (UAVs) that can monitor large farms. Using such technologies, diseases are diagnosed indirectly by detecting changes in the color, texture, and temperature of crop leaves. In this context, intelligent agricultural machines and robots can detect crop diseases at an early stage and monitor disease development remotely [108,109]. Meanwhile, aerial remote sensing (RS) using UAVs or unmanned aerial systems with intelligent vision systems is an efficient and inexpensive way of detecting diseases in crops [108,109,110,111,112,113]. It is reported that the integration of RGB, multispectral, hyperspectral, fluorescence, and thermal infrared imaging sensors, coupled with efficient algorithms on unmanned aerial vehicles (UAVs), enables effective detection, differentiation, and quantification of the severity of symptoms induced by diverse pathogens under field conditions [114,115]. It has been shown that these methods can achieve reliable diagnosis in cereal crops, such as rice [116], corn [117], and wheat [118,119]; vegetables, such as grapevines [120], potatoes [121], soybeans [122], and tomatoes [123]; and forests, such as pine forests [108]. The combination of imaging obtained by drones with artificial intelligence algorithms, such as machine learning, is a promising new approach that not only enables early and accurate diagnosis of crop diseases but also improves crop yields while reducing the cost of disease treatment [124]. Utilizing RS technology to retrieve and gather data, encompassing meteorological information as well as the properties of the earth’s surface and soil, and offering timely feedback, holds significant promise as an effective approach for diagnosing fungal crop diseases in the context of climate change [125] (Table 3).

4.2. Prevention and Control of Crop Fungal Diseases

4.2.1. Breeding Measures for Disease Resistance

Disease resistance breeding is a method of breeding new crop varieties that develop strong resistance to diseases through targeted selection or alteration of certain genotypes. It is one of the most efficient and economical measures to cope with crop diseases. However, improving the disease resistance of crops can simultaneously affect their yield [126]. It has been shown that disease resistance breeding enhances Phytophthora blight resistance while simultaneously reducing Rhizobia colonization, resulting in reduced crop yields [127]. High-quality resistance results in the targeted selection of pathogens, while the speed and scale of pathogen spread increase under extreme climatic conditions. Moreover, research devoted to particular resistant varieties is often overtaken by the emergence of pathogens with greater pathogenicity [128].

4.2.2. Agronomic Measures

Agronomic measures involve the creation of environmental conditions that promote crop growth and the survival and reproduction of beneficial bacteria, but that inhibit the occurrence of pathogenic fungi. Such measures can involve practices such as fertilization, irrigation, and tillage. The application of fertilizer to the soil can change its physical and chemical properties and create an environment suitable for the growth of beneficial microorganisms. The application of chitin amendments to the soil was reported to contribute to soil carbon and nitrogen cycling [129]. Meanwhile, the application of cow dung after ammonia fumigation was found to reduce the abundance of Fusarium spinosum in soil and its infestation in bananas by approximately 55% [130]. Although irrigation can greatly reduce the negative effects of drought [131], there is a lack of effective agronomic measures to cope with disease outbreaks due to climatic extremes of rainfall and flooding; agronomic measures such as crop rotation and intercropping do not have effects that are rapid enough to control fungal disease in the current season [132], and although deep tillage may promote the onset of, for example, leaf spot disease in tea trees [133], the process of applying fertilizers is labor-intensive and time-consuming [134] and fertilizers pose the risk of nutrient leaching [135]. The greatest pressure on irrigation is the severe shortage of freshwater resources available for this purpose [136].

4.2.3. Chemical Control

Chemical control, which involves killing pathogenic bacteria using chemical pesticides to avoid crop damage, is a common method of managing fungal disease and is used for both disease prevention and treatment of diseased crops [137,138,139]. Chemicals play an important role in increasing crop yield and quality, improving food safety, reducing microbial toxins, and extending the shelf life of crops [140,141]. However, chemicals can have harmful effects on plant and animal health and nature [142,143,144]. The application of pesticides poisons organisms in the soil and water bodies and reduces soil biodiversity [145]. A previous study showed that higher spraying of fungicide reduces the diversity of Xylaria spp. isolates, which are beneficial to crops [146]. It has also been shown that penthiopyrad induces oxidative damage and lipid metabolism, causes mitochondrial dysfunction, and leads to apoptosis in fish [147]. The intensive use of chemicals has also been found to lead to increased pathogen resistance [148], and long-term pesticide application has significantly reduced the effectiveness of control of Zymoseptoria tritici, Colletotrichum falcatum, and Venturia inaequalis [149,150]. Moreover, with climate extremes, such as flooding, more than 90% of pesticides are lost in the field, resulting in serious risks to ecosystems. Some pesticides may even exert effects lasting for decades [151,152].

4.2.4. Biological Control

Biological control, which entails the utilization of organisms like crops, insects, and microorganisms, serves as a natural means to mitigate a diverse range of diseases triggered by pathogens [153], is considered a safe and environmentally friendly strategy that can reduce or eliminate the utilization of chemical pesticides [154]. The main forms of biological control involve the application of microbial or bio-organic fertilizers and bio-antagonistic fungicides to the soil. In terms of the microorganisms used for biological control, the main ones include bacteria such as Pseudomonas spp. and Bacillus spp. [155], fungi such as Penicillium spp. and Trichoderma spp., and actinomycetes such as Streptomyces spp. Regarding the mechanisms by which biocontrol bacteria exert their effects, these include the formation of biofilm by Bacillus spp. to promote crop growth, improvement of the microbial community in the soil, and inhibition of the growth of pathogenic bacteria [156]. In terms of how biocontrol fungi work, they can induce crop resistance, produce antimicrobial substances against pathogenic fungi (e.g., iron carriers, volatile organic compounds, solubilizing enzymes), and even occupy ecological niches in advance. For example, it was reported that Chromolaena odorata not only increases the height and shoot/root dry weights of melon plants to promote crop development, but also inhibits the wilt pathogen Fusarium oxysporum by 90% [157]. However, biological control has the shortcoming that the microorganisms used are susceptible to environmental influences, especially in extreme climatic conditions such as drought and high temperatures, leading to unstable prevention and control effects during the application of microbial agents.

4.2.5. Ecological Regulation

In the context of global climate change and the increasing frequency of extreme weather events, traditional singular control measures have become inadequate in effectively preventing and controlling fungal diseases in crops. At its core, ecological control involves a systematic approach to provide a favorable environment for healthy crop growth and maintain the dynamic balance among crop–biology–soil (Figure 2). Soil health is linked to crop health. Heavy metal-stressed vetiver fractionates heavy metals in the soil by secreting organic acids, while raising the level of organic carbon and the pH of soil [158]. Crops can influence the climate by regulating root secretions to reduce nitrogen loss and the carbon footprint, and also by recruiting beneficial microorganisms that enhance the ability to suppress pathogens [159]. The warming of the climate and N2 and CO2 also alter crop–soil interactions [160], while elevated CO2 concentration indirectly affects the size of the population of microbes in the soil [161] and its diversity [162] through physicochemical properties such as soil temperature, moisture, and pH, as well as crop root morphology and root secretions [163]. Microorganisms can inhibit crop diseases by fixing nitrogen [164] and promoting crop growth [165,166], or even by changing the structure of the microbiome from a dysfunctional to a healthy state by altering environmental conditions [167]. The release of metabolites from maize roots affects the composition of root-associated microbiota [168], and the excretion of taxifolin by tomato plants serves as a catalyst for the attraction and recruitment of beneficial bacterial species [169]. The disadvantages of ecological regulation are the complexity of its application and the long time it takes to obtain results.
Effective responses to crop fungal diseases under global climate change conditions require a combination of control measures to realize the dynamic balance of crop–biology–soil, and the capacity of various control measures to enable adaptation to climate change should be fully exploited, such as improving the physicochemical properties of soil and reducing the relative abundance of soil pathogens by performing supplementation with soil conditioning agents, such as biochar, when microbial fungicides are applied [170]. Immobilization of microorganisms in materials can also reduce their exposure to extreme climatic conditions and improve environmental resilience [171]. Meanwhile, the intensive use of multidisciplinary tools, such as varietal performance prediction [172], can help develop new varieties that can adapt to climate change. Moreover, microbial pesticides or nanobiopesticides derived from microorganisms, such as bacteria, fungi, viruses, protozoa, and algae, are being intensively explored to control crop diseases. In this context, environmentally friendly and green control measures also have great potential, such as the application of biopesticides prepared from wood mold for the control of root rot of chickpea [173] and the application of biocontrol agents such as a Trichoderma and chitosan-polyethylene glycol (PEG) hybrid system for seed treatment [174]. Nanobiopesticides have beneficial physicochemical properties, such as a small particle size, easy reactivity, large surface area, clear biological interactions with crops, and clear transport and fate in the environment (Table 4).

5. Summary and Outlook

With advancement in global climate change, extreme climatic events, such as high temperatures, droughts, and floods, are becoming more frequent and more severe. Meanwhile, outbreaks of fungal diseases of crops are becoming more frequent and serious and disrupting the dynamic balance among crops, organisms, and the soil. Intensifying climate change necessitates the development of new data acquisition technologies and diagnostic methods, such as RS, combined with artificial intelligence coupling technology, to collect and analyze disease data in an accurate, timely, and efficient manner on the basis of existing methods for monitoring and diagnosing crop fungal diseases. After determining the areas affected by disease, the ecological regulation can be used to organize the implementation of ecological control measures and traditional control measures, apply the control technology in the context of climate change, maintain the health of the soil and crop, protect the diversity of the overall community of microorganisms, and slow down the harm caused by crop fungal diseases in association with climate change. The ecological management of crop–biological–soil dynamics is considered to be an effective measure to combat fungal diseases in the future, and this new concept promotes the green development of agriculture and mitigates the damage caused to crops by fungal diseases under extreme climatic conditions.

Author Contributions

Conceptualization, J.Z. and X.Z.; methodology, J.Z., X.Z., and Z.Q.; validation, J.Z., X.Z., Z.Q., and C.Z.; investigation, J.Z., C.Z., F.W., and T.G.; resources, J.Z., F.W., Y.Y., and J.L.; data curation, J.Z. and Z.Q.; writing—original draft preparation, J.Z. and Z.Q.; visualization, J.Z.; supervision, J.Z., Z.Q., and F.W.; funding acquisition, J.Z. and F.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research is financially supported by National Key Research and Development Program Projects (No. 2022YFD1901305-4), Yunnan Fundamental Research Projects (202101AT070002), Wang Feng Expert Primary-level Workstation, Yunnan Province.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Delgado-Baquerizo, M.; Guerra, C.A.; Cano-Díaz, C.; Egidi, E.; Wang, J.; Eisenhauer, N.; Singh, B.K.; Maestre, F.T. The Proportion of Soil-Borne Pathogens Increases with Warming at the Global Scale. Nat. Clim. Chang. 2020, 10, 550–554. [Google Scholar] [CrossRef]
  2. Li, E.; Ling, J.; Wang, G.; Xiao, J.; Yang, Y.; Mao, Z.; Wang, X.; Xie, B. Comparative Proteomics Analyses of Two Races of Fusarium oxysporum f. sp. Conglutinans that Differ in Pathogenicity. Sci. Rep. 2015, 5, 13663. [Google Scholar] [CrossRef]
  3. Narayanasamy, P. Microbial Plant Pathogens-Detection and Disease Diagnosis; Springer: Berlin/Heidelberg, Germany, 2011. [Google Scholar] [CrossRef]
  4. Brefort, T.; Doehlemann, G.; Mendoza-Mendoza, A.; Reissmann, S.; Djamei, A.; Kahmann, R. Ustilago Maydis as a Pathogen. Annu. Rev. Phytopathol. 2009, 47, 423–445. [Google Scholar] [CrossRef]
  5. Nourozian, J.; Etebarian, H.R.; Khodakaramian, G. Biological Control of Fusarium graminearum on Wheat by Antagonistic Bacteria. Songklanakarin J. Sci. Technol. 2006, 28 (Suppl. S1), 29–38. [Google Scholar]
  6. Tamura, T.; Shinzato, N.; Ito, M.; Ueno, M. Microbial Secondary Metabolite Induction of Abnormal Appressoria Formation Mediates Control of Rice Blast Disease Caused Bymagnaporthe Oryzae. J. Phytopathol. 2019, 167, 156–162. [Google Scholar] [CrossRef]
  7. Karelov, A.; Kozub, N.; Sozinova, O.; Pirko, Y.; Sozinov, I.; Yemets, A.; Blume, Y. Wheat Genes Associated with Different Types of Resistance against Stem Rust (Puccinia graminis Pers.). Pathogens 2022, 11, 1157. [Google Scholar] [CrossRef]
  8. Asibi, A.E.; Chai, Q.; Coulter, J.A. Rice Blast: A Disease with Implications for Global Food Security. Agronomy 2019, 9, 451. [Google Scholar] [CrossRef]
  9. Su, J.; Zhao, J.; Zhao, S.; Li, M.; Pang, S.; Kang, Z.; Zhen, W.; Chen, S.; Chen, F.; Wang, X. Genetics of Resistance to Common Root Rot (Spot Blotch), Fusarium Crown Rot, and Sharp Eyespot in Wheat. Front. Genet. 2021, 12, 699342. [Google Scholar] [CrossRef]
  10. Pennisi, E. Armed and Dangerous. Science 2010, 327, 804–805. [Google Scholar] [CrossRef]
  11. Lobell, D.; Burke, M.; Tebaldi, C.; Mastrandrea, M.D.; Falcon, W.; Naylor, R.L. Prioritizing Climate Change Adaptation Needs for Food Security in 2030. Science 2008, 319, 607–610. [Google Scholar] [CrossRef]
  12. Godfray, H.C.; Beddington, J.R.; Crute, I.R.; Haddad, L.; Lawrence, D.; Muir, J.F.; Pretty, J.; Robinson, S.; Thomas, S.M.; Toulmin, C. Food Security: The Challenge of Feeding 9 Billion People. Science 2010, 327, 812–818. [Google Scholar] [CrossRef] [PubMed]
  13. Alexandratos, N.; Bruinsma, J. World Agriculture Towards 2030/2050: The 2012 Revision; FAO: Rome, Italy, 2012. [Google Scholar]
  14. Challinor, A.J.; Watson, J.E.M.; Lobell, D.; Howden, S.M.; Smith, D.R.; Chhetri, N. A Meta-Analysis of Crop Yield under Climate Change and Adaptation. Nat. Clim. Chang. 2014, 4, 287–291. [Google Scholar] [CrossRef]
  15. Hijmans, R.J. The Effect of Climate Change on Global Potato Production. Am. J. Potato Res. 2003, 80, 271–279. [Google Scholar] [CrossRef]
  16. Reisinger, A.; Kitching, R.; Chiew, F.; Hughes, L.; Newton, P.; Schuster, S.; Tait, A.; Whetton, P.; Barnett, J.; Becken, S.; et al. Climate Change 2014: Impacts, Adaptation, and Vulnerability. Working Group II Contribution to the Fifth Assessment Report of the IPCC: Australasia Intergovernmental Panel on Climate Change; Cambridge University Press: Cambridge, UK, 2014. [Google Scholar]
  17. Rogelj, J.; den Elzen, M.; Höhne, N.; Fransen, T.; Fekete, H.; Winkler, H.; Schaeffer, R.; Sha, F.; Riahi, K.; Meinshausen, M. Paris Agreement Climate Proposals Need a Boost to Keep Warming Well below 2 °C. Nature 2016, 534, 631–639. [Google Scholar] [CrossRef] [PubMed]
  18. Singh, N.; Anand, G.; Kapoor, R. Incidence and Severity of Fungal Diseases of Safflower in India. Crop Prot. 2019, 125, 104905. [Google Scholar] [CrossRef]
  19. Salunkhe, V.N.; Gedam, P.; Pradhan, A.; Gaikwad, B.; Kale, R.; Gawande, S. Concurrent Waterlogging and Anthracnose-Twister Disease in Rainy-Season Onions (Allium cepa): Impact and Management. Front. Microbiol. 2022, 13, 1063472. [Google Scholar] [CrossRef] [PubMed]
  20. Romero, F.; Cazzato, S.; Walder, F.; Vogelgsang, S.; Bender, S.F.; van der Heijden, M.G.A. Humidity and High Temperature Are Important for Predicting Fungal Disease Outbreaks Worldwide. New Phytol. 2022, 234, 1553–1556. [Google Scholar] [CrossRef] [PubMed]
  21. Haddoudi, I.; Mhadhbi, H.; Gargouri, M.; Barhoumi, F.; Romdhane, S.B.; Mrabet, M. Occurrence of Fungal Diseases in Faba Bean (Vicia faba L.) under Salt and Drought Stress. Eur. J. Plant Pathol. 2021, 159, 385–398. [Google Scholar] [CrossRef]
  22. Feulefack, J.; Khan, A.; Forastiere, F.; Sergi, C.M. Parental Pesticide Exposure and Childhood Brain Cancer: A Systematic Review and Meta-Analysis Confirming the IARC/WHO Monographs on Some Organophosphate Insecticides and Herbicides. Children 2021, 8, 1096. [Google Scholar] [CrossRef] [PubMed]
  23. Al Naggar, Y.; Wubet, T. Chronic Exposure to Pesticides Disrupts the Bacterial and Fungal Co-Existence and the Cross-Kingdom Network Characteristics of Honey Bee Gut Microbiome. Sci. Total Environ. 2024, 906, 167530. [Google Scholar] [CrossRef] [PubMed]
  24. Alptekin, B.; Langridge, P.; Budak, H. Abiotic Stress Mirnomes in the Triticeae. Funct. Integr. Genom. 2017, 17, 145–170. [Google Scholar] [CrossRef] [PubMed]
  25. Naing, A.H.; Kim, C. Abiotic Stress-Induced Anthocyanins in Plants: Their Role in Tolerance to Abiotic Stresses. Physiol. Plant. 2021, 172, 1711–1723. [Google Scholar] [CrossRef] [PubMed]
  26. Schreiner, R.P.; Tarara, J.M.; Smithyman, R.P. Deficit Irrigation Promotes Arbuscular Colonization of Fine Roots by Mycorrhizal Fungi in Grapevines (Vitis vinifera L.) In an Arid Climate. Mycorrhiza 2007, 17, 551–562. [Google Scholar] [CrossRef] [PubMed]
  27. Chilakala, A.R.; Mali, K.V.; Irulappan, V.; Patil, B.S.; Pandey, P.; Rangappa, K.; Ramegowda, V.; Kumar, M.N.; Puli, C.O.R.; Mohan-Raju, B.; et al. Combined Drought and Heat Stress Influences the Root Water Relation and Determine the Dry Root Rot Disease Development Under Field Conditions: A Study Using Contrasting Chickpea Genotypes. Front. Plant Sci. 2022, 13, 890551. [Google Scholar] [CrossRef] [PubMed]
  28. Bidzinski, P.; Ballini, E.; Ducasse, A.; Michel, C.; Zuluaga, P.; Genga, A.; Chiozzotto, R.; Morel, J.B. Transcriptional Basis of Drought-Induced Susceptibility to the Rice Blast Fungus Magnaporthe oryzae. Front. Plant Sci. 2016, 7, 1558. [Google Scholar] [CrossRef] [PubMed]
  29. Choi, H.-K.; Iandolino, A.; Silva, F.; Cook, D. Water Deficit Modulates the Response of Vitis vinifera to the Pierce’s Disease Pathogen Xylella fastidiosa. Mol. Plant-Microbe Interact. MPMI 2013, 26, 643–657. [Google Scholar] [CrossRef] [PubMed]
  30. Jat, R.A.; Wani, S.P.; Sahrawat, K.L. Conservation Agriculture in the Semi-Arid Tropics: Prospects and Problems. Adv. Agron. 2012, 117, 191–273. [Google Scholar]
  31. Radzikowski, P.; Jończyk, K.; Feledyn-Szewczyk, B.; Jóźwicki, T. Assessment of Resistance of Different Varieties of Winter Wheat to Leaf Fungal Diseases in Organic Farming. Agriculture 2023, 13, 875. [Google Scholar] [CrossRef]
  32. Pandey, P.; Irulappan, V.; Bagavathiannan, M.V.; Senthil-Kumar, M. Impact of Combined Abiotic and Biotic Stresses on Plant Growth and Avenues for Crop Improvement by Exploiting Physio-Morphological Traits. Front. Plant Sci. 2017, 8, 537. [Google Scholar] [CrossRef] [PubMed]
  33. Shoaib, A.; Meraj, S.; Nafisa, N.; Khan, K.; Javaid, A. Influence of Salinity and Fusarium Oxysporum as the Stress Factors on Morpho-Physiological and Yield Attributes in Onion. Physiol. Mol. Biol. Plants 2018, 24, 1093–1101. [Google Scholar] [CrossRef] [PubMed]
  34. Chojak-Koźniewska, J.; Linkiewicz, A.M.; Sowa, S.; Radzioch, M.A.; Kuźniak, E. Interactive Effects of Salt Stress and Pseudomonas syringae pv. lachrymans Infection in Cucumber: Involvement of Antioxidant Enzymes, Abscisic acid and Salicylic Acid. Environ. Exp. Bot. 2017, 136, 9–20. [Google Scholar]
  35. Al-Sadi, A.M.; Al-masoudi, R.S.; Al-Habsi, N.; Al-Said, F.A.-J.; Al-Rawahy, S.A.; Ahmed, M.; Deadman, M.L. Effect of Salinity on Pythium Damping-Off of Cucumber and on the Tolerance of Pythium aphanidermatum. Plant Pathol. 2010, 59, 112–120. [Google Scholar] [CrossRef]
  36. Allard, S.M.; Ottesen, A.R.; Micallef, S.A. Rain Induces Temporary Shifts in Epiphytic Bacterial Communities of Cucumber and Tomato Fruit. Sci. Rep. 2020, 10, 1765. [Google Scholar] [CrossRef] [PubMed]
  37. Czarnecka, D.; Czubacka, A.; Agacka-Mołdoch, M.; Trojak-Goluch, A.; Księżak, J. The Occurrence of Fungal Diseases in Maize in Organic Farming Versus an Integrated Management System. Agronomy 2022, 12, 558. [Google Scholar] [CrossRef]
  38. Chávez-Arias, C.C.; Gómez-Caro, S.; Restrepo-Díaz, H. Physiological, Biochemical and Chlorophyll Fluorescence Parameters of Physalis peruviana L. Seedlings Exposed to Different Short-Term Waterlogging Periods and Fusarium Wilt Infection. Agronomy 2019, 9, 213. [Google Scholar] [CrossRef]
  39. Iliff, G.J.; Mukherjee, R.; Gruszewski, H.A.; Schmale Iii, D.G.; Jung, S.; Boreyko, J.B. Phase-Change-Mediated Transport and Agglomeration of Fungal Spores on Wheat Awns. J. R. Soc. Interface 2022, 19, 20210872. [Google Scholar] [CrossRef] [PubMed]
  40. Gopi, R.; Chandran, K.; Ramesh Sundar, A.; Nisha, M.; Mahendran, B.; Keerthana; Jayaraman, S.; Viswanathan, R. Occurrence of False Floral Smut in Sugarcane Inflorescence and Associated Weather Variables. SugarTech 2023, 25, 1411–1418. [Google Scholar] [CrossRef]
  41. Nene, W.; Kapinga, F.; Shomari, S.; Assenga, B. Cashew Leaf and Nut Blight Disease Outbreaks under Unimodal Rainfall Pattern in Tanzania. J. Plant Pathol. 2022, 104, 929–938. [Google Scholar] [CrossRef]
  42. Khaliq, I.; Moore, K.; Sparks, A.H. The Relationship between Natural Rain Intensity and Ascochyta Blight in Chickpea Development. Eur. J. Plant Pathol. 2022, 164, 313–323. [Google Scholar] [CrossRef] [PubMed]
  43. Rollano-Peñaloza, O.M.; Palma-Encinas, V.; Widell, S.; Mollinedo, P.; Rasmusson, A.G. The Disease Progression and Molecular Defense Response in Chenopodium Quinoa Infected with Peronospora Variabilis, the Causal Agent of Quinoa Downy Mildew. Plants 2022, 11, 2946. [Google Scholar] [CrossRef] [PubMed]
  44. Barro, M.; Kassankogno, A.I.; Wonni, I.; Sérémé, D.; Somda, I.; Kaboré, H.K.; Béna, G.; Brugidou, C.; Tharreau, D.; Tollenaere, C. Spatiotemporal Survey of Multiple Rice Diseases in Irrigated Areas Compared to Rainfed Lowlands in the Western Burkina Faso. Plant Dis. 2021, 105, 3889–3899. [Google Scholar] [CrossRef] [PubMed]
  45. Desaint, H.; Aoun, N.; Deslandes, L.; Vailleau, F.; Roux, F.; Berthomé, R. Fight Hard or Die Trying: When Plants Face Pathogens under Heat Stress. New Phytol. 2021, 229, 712–734. [Google Scholar] [CrossRef] [PubMed]
  46. Ji, T.; Salotti, I.; Altieri, V.; Li, M.; Rossi, V. Temperature-Dependent Growth and Spore Germination of Fungi Causing Grapevine Trunk Diseases: Quantitative Analysis of Literature Data. Plant Dis. 2023, 107, 1386–1398. [Google Scholar] [CrossRef] [PubMed]
  47. Songy, A.; Fernandez, O.; Clément, C.; Larignon, P.; Fontaine, F. Grapevine Trunk Diseases under Thermal and Water Stresses. Planta 2019, 249, 1655–1679. [Google Scholar] [CrossRef] [PubMed]
  48. Kaur, S.; Barakat, R.; Kaur, J.; Epstein, L. The Effect of Temperature on Disease Severity and Growth of Fusarium oxysporum f. sp. Apii Races 2 and 4 in Celery. Phytopathology 2022, 112, 364–372. [Google Scholar] [CrossRef] [PubMed]
  49. Yan, H.; Nelson, B.D. Effect of Temperature on Fusarium solani and F. Tricinctum Growth and Disease Development in Soybean. Can. J. Plant Pathol. 2020, 42, 527–537. [Google Scholar] [CrossRef]
  50. Shakya, S.K.; Goss, E.M.; Dufault, N.S.; van Bruggen, A.H. Potential Effects of Diurnal Temperature Oscillations on Potato Late Blight with Special Reference to Climate Change. Phytopathology 2015, 105, 230–238. [Google Scholar] [CrossRef] [PubMed]
  51. Shafiekhani, S.; Wilson, S.A.; Atungulu, G.G. Impacts of Storage Temperature and Rice Moisture Content on Color Characteristics of Rice from Fields with Different Disease Management Practices. J. Stored Prod. Res. 2018, 78, 89–97. [Google Scholar] [CrossRef]
  52. Odebode, A.C.; Unachukwu, N.E. Effect of Storage Environment on Carrot Root Rots and Biochemical Changes During Storage. Z. Für Leb. Und-Forsch. A 1997, 205, 277–281. [Google Scholar] [CrossRef]
  53. Casagrande, E.; Génard, M.; Lurol, S.; Charles, F.; Bevacqua, D.; Martinetti, D.; Lescourret, F. Brown Rot Disease in Stored Nectarines: Modeling the Combined Effects of Preharvest and Storage Conditions. Phytopathology 2022, 112, 1575–1583. [Google Scholar] [CrossRef] [PubMed]
  54. Meshram, S.; Adhikari, T.B. Microbiome-Mediated Strategies to Manage Major Soil-Borne Diseases of Tomato. Plants 2024, 13, 364. [Google Scholar] [CrossRef] [PubMed]
  55. Mendes, L.W.; Raaijmakers, J.M.; de Hollander, M.; Mendes, R.; Tsai, S.M. Influence of Resistance Breeding in Common Bean on Rhizosphere Microbiome Composition and Function. ISME J. 2018, 12, 212–224. [Google Scholar] [CrossRef] [PubMed]
  56. Adolf, B.; Andrade-Piedra, J.; Bittara Molina, F.; Przetakiewicz, J.; Hausladen, H.; Kromann, P.; Lees, A.; Lindqvist-Kreuze, H.; Perez, W.; Secor, G.A. Fungal, Oomycete, and Plasmodiophorid Diseases of Potato. In The Potato Crop: Its Agricultural, Nutritional and Social Contribution to Humankind; Campos, H., Ortiz, O., Eds.; Springer International Publishing: Cham, Switzerland, 2020; pp. 307–350. [Google Scholar] [CrossRef]
  57. Guan, Z.; Biswas, T.; Wu, F. The U.S. Tomato Industry: An Overview of Production and Trade. EDIS 2018, 2018. [Google Scholar] [CrossRef]
  58. Panth, M.; Hassler, S.C.; Baysal-Gurel, F. Methods for Management of Soilborne Diseases in Crop Production. Agriculture 2020, 10, 16. [Google Scholar] [CrossRef]
  59. Zhang, Y.; Ye, C.; Su, Y.; Peng, W.; Lu, R.; Liu, Y.; Huang, H.; He, X.; Yang, M.; Zhu, S. Soil Acidification Caused by Excessive Application of Nitrogen Fertilizer Aggravates Soil-Borne Diseases: Evidence from Literature Review and Field Trials. Agric. Ecosyst. Environ. 2022, 340, 108176. [Google Scholar] [CrossRef]
  60. Schauberger, B.; Archontoulis, S.; Arneth, A.; Balkovic, J.; Ciais, P.; Deryng, D.; Elliott, J.; Folberth, C.; Khabarov, N.; Müller, C.; et al. Consistent Negative Response of US Crops to High Temperatures in Observations and Crop Models. Nat. Commun. 2017, 8, 13931. [Google Scholar] [CrossRef] [PubMed]
  61. Cheng, W.; Lin, M.; Qiu, M.; Kong, L.; Xu, Y.; Li, Y.; Wang, Y.; Ye, W.; Dong, S.; He, S.; et al. Chitin Synthase Is Involved in Vegetative Growth, Asexual Reproduction and Pathogenesis of Phytophthora capsici and Phytophthora sojae. Environ. Microbiol. 2019, 21, 4537–4547. [Google Scholar] [CrossRef] [PubMed]
  62. You, M.P.; Lamichhane, J.R.; Aubertot, J.-N.; Barbetti, M.J. Understanding Why Effective Fungicides Against Individual Soilborne Pathogens Are Ineffective with Soilborne Pathogen Complexes. Plant Dis. 2019, 104, 904–920. [Google Scholar] [CrossRef] [PubMed]
  63. Barbetti, M.J.; Khan, T.N.; Pritchard, I.; Lamichhane, J.R.; Aubertot, J.N.; Corrales, D.C.; You, M.P. Challenges With Managing Disease Complexes During Application of Different Measures Against Foliar Diseases of Field Pea. Plant Dis. 2021, 105, 616–627. [Google Scholar] [CrossRef] [PubMed]
  64. Back, M.; Haydock, P.; Jenkinson, P. Disease Complexes Involving Plant Parasitic Nematodes and Soilborne Pathogens. Plant Pathol. 2002, 51, 683–697. [Google Scholar] [CrossRef]
  65. Ahmadi, M.; Mirakhorli, N.; Erginbas-Orakci, G.; Ansari, O.; Braun, H.-J.; Paulitz, T.C.; Dababat, A. Interactions among Cereal cyst Nematode Heterodera filipjevi, Dryland crown rot Fusarium culmorum, and Drought on Grain Yield Components and Disease Severity in Bread wheat. Can. J. Plant Pathol. 2021, 44, 415–431. [Google Scholar] [CrossRef]
  66. You, M.P.; Rensing, K.; Renton, M.; Barbetti, M.J. Modeling Effects of Temperature, Soil, Moisture, Nutrition and Variety As Determinants of Severity of Pythium Damping-Off and Root Disease in Subterranean Clover. Front. Microbiol. 2017, 8, 2223. [Google Scholar] [CrossRef] [PubMed]
  67. Gibert, S.; Edel-Hermann, V.; Gautheron, E.; Gautheron, N.; Bernaud, E.; Sol, J.M.; Capelle, G.P.J.; Galland, R.; Bardon-Debats, A.; Lambert, C.; et al. Identification, Pathogenicity and Community Dynamics of Fungi and Oomycetes Associated with Pea Root Rot in Northern France. Plant Pathol. 2022, 71, 1550–1569. [Google Scholar] [CrossRef]
  68. Haas, D.; Ilieva, M.; Fritz, T.; Galler, H.; Habib, J.; Kriso, A.; Kropsch, M.; Ofner-Kopeinig, P.; Reinthaler, F.F.; Strasser, A.; et al. Background Concentrations of Airborne, Culturable Fungi and Dust Particles in Urban, Rural and Mountain Regions. Sci. Total Environ. 2023, 892, 164700. [Google Scholar] [CrossRef] [PubMed]
  69. Macleod, A.; Pautasso, M.; Jeger, M.; Haines-Young, R. Evolution of the International Regulation of Plant Pest and Challenges for Future Plant Health. Food Secur. 2010, 2, 49–70. [Google Scholar] [CrossRef]
  70. Wellings, C.; Mcintosh, R.; Walker, J. Puccinia striiformis f.sp. Tritici in Eastern Australia Possible Means of Entry and Implications for Plant Quarantine. Plant Pathol. 2007, 36, 239–241. [Google Scholar] [CrossRef]
  71. Ding, Y.; Cuddy, W.S.; Wellings, C.R.; Zhang, P.; Thach, T.; Hovmøller, M.S.; Qutob, D.; Brar, G.S.; Kutcher, H.R.; Park, R.F. Incursions of Divergent Genotypes, Evolution of Virulence and Host Jumps Shape a Continental Clonal Population of the Stripe Rust Pathogen Puccinia striiformis. Mol. Ecol. 2021, 30, 6566–6584. [Google Scholar] [CrossRef] [PubMed]
  72. Visser, B.; Meyer, M.; Park, R.F.; Gilligan, C.A.; Burgin, L.E.; Hort, M.C.; Hodson, D.P.; Pretorius, Z.A. Microsatellite Analysis and Urediniospore Dispersal Simulations Support the Movement of Puccinia graminis f. sp. Tritici from Southern Africa to Australia. Phytopathology 2019, 109, 133–144. [Google Scholar] [CrossRef] [PubMed]
  73. Sharma-Poudyal, D.; Chen, X.M.; Wan, A.M.; Zhan, G.M.; Kang, Z.S.; Cao, S.Q.; Jin, S.L.; Morgounov, A.; Akin, B.; Mert, Z.; et al. Virulence Characterization of International Collections of the Wheat Stripe Rust Pathogen, Puccinia striiformis f. sp. Tritici. Plant Dis 2013, 97, 379–386. [Google Scholar] [CrossRef] [PubMed]
  74. Ali, S.; Gladieux, P.; Leconte, M.; Gautier, A.; Justesen, A.F.; Hovmøller, M.S.; Enjalbert, J.; de Vallavieille-Pope, C. Origin, Migration Routes and Worldwide Population Genetic Structure of the Wheat Yellow Rust Pathogen Puccinia striiformis f. sp. Tritici. PLoS Pathog. 2014, 10, e1003903. [Google Scholar] [CrossRef] [PubMed]
  75. Picornell, A.; Rojo, J.; Trigo, M.M.; Ruiz-Mata, R.; Lara, B.; Romero-Morte, J.; Serrano-García, A.; Pérez-Badia, R.; Gutiérrez-Bustillo, M.; Cervigón-Morales, P.; et al. Environmental Drivers of the Seasonal Exposure to Airborne Alternaria spores in Spain. Sci. Total Environ. 2022, 823, 153596. [Google Scholar] [CrossRef] [PubMed]
  76. Sindt, C.; Besancenot, J.-P.; Thibaudon, M. Airborne Cladosporium Fungal Spores and Climate Change in France. Aerobiologia 2016, 32, 53–68. [Google Scholar] [CrossRef]
  77. Estève, R.S.; Baisnée, D.; Guinot, B.; Sodeau, J.; O’Connor, D.J.; Belmonte, J.; Besancenot, J.-P.; Petit, J.-E.; Thibaudon, M.; Oliver, G.; et al. Variability and Geographical Origin of Five Years Airborne Fungal Spore Concentrations Measured at Saclay, France from 2014 to 2018. Remote Sens. 2019, 11, 1671. [Google Scholar] [CrossRef]
  78. Urban, J.; Lebeda, A. Variation of Fungicide Resistance in Czech Populations of Pseudoperonospora cubensis. J. Phytopathol. 2007, 155, 143–151. [Google Scholar] [CrossRef]
  79. Zhanbin, S.; Yu, S.; Hu, Y.; Wen, Y. Biological Control of the Cucumber Downy Mildew Pathogen Pseudoperonospora cubensis. Horticulturae 2022, 8, 410. [Google Scholar] [CrossRef]
  80. Lamichhane, J.R.; Bischoff-Schaefer, M.; Bluemel, S.; Dachbrodt-Saaydeh, S.; Dreux, L.; Jansen, J.P.; Kiss, J.; Köhl, J.; Kudsk, P.; Malausa, T.; et al. Identifying Obstacles and Ranking Common Biological Control Research Priorities for Europe to Manage Most Economically Important Pests in Arable, Vegetable and Perennial Crops. Pest Manag. Sci. 2017, 73, 14–21. [Google Scholar] [CrossRef] [PubMed]
  81. Bowen, J.K.; Mesarich, C.H.; Bus, V.G.; Beresford, R.M.; Plummer, K.M.; Templeton, M.D. Venturia Inaequalis: The Causal Agent of Apple Scab. Mol. Plant Pathol. 2011, 12, 105–122. [Google Scholar] [CrossRef] [PubMed]
  82. González-Domínguez, E.; Armengol, J.; Rossi, V. Biology and Epidemiology of Venturia Species Affecting Fruit Crops: A Review. Front. Plant Sci. 2017, 8, 1496. [Google Scholar] [CrossRef]
  83. Jha, G.; Thakur, K.; Thakur, P. The Venturia Apple Pathosystem: Pathogenicity Mechanisms and Plant Defense Responses. J. Biomed. Biotechnol. 2009, 2009, 680160. [Google Scholar] [CrossRef] [PubMed]
  84. Abuley, I.K.; Nielsen, B.J. Evaluation of Models to Control Potato Early Blight (Alternaria solani) in Denmark. Crop Prot. 2017, 102, 118–128. [Google Scholar] [CrossRef]
  85. Meno, L.; Escuredo, O.; Rodríguez-Flores, M.S.; Seijo, M.C. Modification of the TOMCAST Model with Aerobiological Data for Management of Potato Early Blight. Agronomy 2020, 10, 1872. [Google Scholar] [CrossRef]
  86. Singh, V.; Shrivastava, A.; Jadon, S.; Wahi, N.; Singh, A.; Sharma, N. Alternaria Diseases of Vegetable Crops and Its Management Control to Reduce the Low Production. Int. J. Agric. Biol. 2015, 7, 834. [Google Scholar]
  87. Campos, H.; Ortiz, O. The Potato Crop: Its Agricultural, Nutritional and Social Contribution to Humankind. In The Potato Crop; Springer: Berlin/Heidelberg, Germany, 2019. [Google Scholar]
  88. Escuredo, O.; Seijo-Rodríguez, A.; Meno, L.; Rodríguez-Flores, M.S.; Seijo, M.C. Seasonal Dynamics of Alternaria during the Potato Growing Cycle and the Influence of Weather on the Early Blight Disease in North-West Spain. Am. J. Potato Res. 2019, 96, 532–540. [Google Scholar] [CrossRef]
  89. Sarita; Buts, A.K.; Singh, R. Seed Borne Mycoflora of Mung Bean (Phaseolus aureus Roxb.) and Its Control by Fungicides. Adv. Appl. Sci. Res. 2014, 5, 8–10. [Google Scholar]
  90. Howell, C.R. Cotton Seedling Preemergence Damping-Off Incited by Rhizopus oryzae and Pythium spp. and Its Biological Control with Trichoderma spp. Phytopathology 2002, 92, 177–180. [Google Scholar] [CrossRef] [PubMed]
  91. Pieczul, K.; Perek, A.; Kubiak, K. Detection of Tilletia caries, Tilletia laevis and Tilletia controversa Wheat Grain Contamination Using Loop-Mediated Isothermal DNA Amplification (LAMP). J. Microbiol. Methods 2018, 154, 141–146. [Google Scholar] [CrossRef] [PubMed]
  92. Mkandawire, L.; Mhango, W.; Saka, V.W.; Juma, S.; Goodman, J.; Brandenburg, R.L.; Jordan, D.L. Influence of Plant Population and Harvest Date on Peanut (Arachis hypogaea) Yield and Aflatoxin Contamination. Peanut Sci. 2021, 48, 33–39. [Google Scholar] [CrossRef]
  93. Pramunadipta, S.; Widiastuti, A.; Wibowo, A.; Priyatmojo, A. Rep-PCR Analysis of Fusarium proliferatum Causing Sheath Rot Disease and Its Relationship to Light, PH, Temperature and Rice Varieties. Arch. Phytopathol. Plant Prot. 2022, 55, 973–990. [Google Scholar] [CrossRef]
  94. Rao, P.J.M.; Pallavi, M.; Bharathi, Y.; Priya, P.B.; Sujatha, P.; Prabhavathi, K. Insights into Mechanisms of Seed Longevity in Soybean: A Review. Front. Plant Sci. 2023, 14, 1206318. [Google Scholar] [CrossRef] [PubMed]
  95. Farber, C.; Mahnke, M.; Sanchez, L.; Kurouski, D. Advanced Spectroscopic Techniques for Plant Disease Diagnostics. A Review. TrAC Trends Anal. Chem. 2019, 118, 43–49. [Google Scholar] [CrossRef]
  96. Genaev, M.A.; Skolotneva, E.S.; Gultyaeva, E.I.; Orlova, E.A.; Bechtold, N.P.; Afonnikov, D.A. Image-Based Wheat Fungi Diseases Identification by Deep Learning. Plants 2021, 10, 1500. [Google Scholar] [CrossRef] [PubMed]
  97. Kindo, A.J.; Tupaki-Sreepurna, A.; Yuvaraj, M. Banana Peel Culture as an Indigenous Medium for Easy Identification of Late-Sporulation Human Fungal Pathogens. Indian J. Med. Microbiol. 2016, 34, 457–461. [Google Scholar] [CrossRef] [PubMed]
  98. Khater, M.; de la Escosura-Muñiz, A.; Merkoçi, A. Biosensors for Plant Pathogen Detection. Biosens. Bioelectron. 2017, 93, 72–86. [Google Scholar] [CrossRef] [PubMed]
  99. Farber, C.; Bryan, R.; Paetzold, L.; Rush, C.; Kurouski, D. Non-Invasive Characterization of Single-, Double- and Triple-Viral Diseases of Wheat with a Hand-Held Raman Spectrometer. Front. Plant Sci. 2020, 11, 01300. [Google Scholar] [CrossRef] [PubMed]
  100. Dyussembayev, K.; Sambasivam, P.; Bar, I.; Brownlie, J.C.; Shiddiky, M.J.A.; Ford, R. Biosensor Technologies for Early Detection and Quantification of Plant Pathogens. Front. Chem. 2021, 9, 636245. [Google Scholar] [CrossRef] [PubMed]
  101. Abu-Khalaf, N.; Salman, M. Detecting Plant Diseases Using Visible/Near Infrared Spectroscopy. NIR News 2013, 24, 12–25. [Google Scholar] [CrossRef]
  102. Larsolle, A.; Hamid Muhammed, H. Measuring Crop Status Using Multivariate Analysis of Hyperspectral Field Reflectance with Application to Disease Severity and Plant Density. Precis. Agric. 2007, 8, 37–47. [Google Scholar] [CrossRef]
  103. Thévenot, D.R.; Toth, K.; Durst, R.A.; Wilson, G.S. Electrochemical Biosensors: Recommended Definitions and Classification. Biosens. Bioelectron. 2001, 16, 121–131. [Google Scholar] [CrossRef]
  104. Neethirajan, S.; Ragavan, K.V.; Weng, X. Agro-Defense: Biosensors for Food from Healthy Crops and Animals. Trends Food Sci. Technol. 2018, 73, 25–44. [Google Scholar] [CrossRef]
  105. Wilson, A.D. Noninvasive Early Disease Diagnosis by Electronic-Nose and Related VOC-Detection Devices. Biosensors 2020, 10, 73. [Google Scholar] [CrossRef] [PubMed]
  106. Li, X.; Guo, L.; Guo, M.; Qi, D.; Zhou, X.; Li, F.; Wu, J. Three Highly Sensitive Monoclonal Antibody-Based Serological Assays for the Detection of Tomato Mottle Mosaic Virus. Phytopathol. Res. 2021, 3, 23. [Google Scholar] [CrossRef]
  107. Gan, Z.; Zhou, Q.a.; Zheng, C.; Wang, J. Challenges and Applications of Volatile Organic Compounds Monitoring Technology in Plant Disease Diagnosis. Biosens. Bioelectron. 2023, 237, 115540. [Google Scholar] [CrossRef] [PubMed]
  108. Qin, J.; Wang, B.; Wu, Y.; Lu, Q.; Zhu, H. Identifying Pine Wood Nematode Disease Using UAV Images and Deep Learning Algorithms. Remote Sens. 2021, 13, 162. [Google Scholar] [CrossRef]
  109. Cui, S.; Ling, P.; Zhu, H.; Keener, H.M. Plant Pest Detection Using an Artificial Nose System: A Review. Sensors 2018, 18, 378. [Google Scholar] [CrossRef] [PubMed]
  110. Martinelli, F.; Scalenghe, R.; Davino, S.; Panno, S.; Scuderi, G.; Ruisi, P.; Villa, P.; Stroppiana, D.; Boschetti, M.; Goulart, L.R.; et al. Advanced methods of plant disease detection. A review. Agron. Sustain. Dev. 2014, 35, 1–25. [Google Scholar] [CrossRef]
  111. Ge, Y.; Thomasson, J.; Sui, R. Remote Sensing of Soil Properties in Precision Agriculture: A Review. Front. Earth Sci. 2011, 5, 229–238. [Google Scholar] [CrossRef]
  112. Shi, Y.; Thomasson, J.A.; Murray, S.C.; Pugh, N.A.; Rooney, W.L.; Shafian, S.; Rajan, N.; Rouze, G.; Morgan, C.L.; Neely, H.L.; et al. Unmanned Aerial Vehicles for High-Throughput Phenotyping and Agronomic Research. PLoS ONE 2016, 11, e0159781. [Google Scholar] [CrossRef] [PubMed]
  113. Herrmann, I.; Bdolach, E.; Montekyo, Y.; Rachmilevitch, S.; Townsend, P.; Karnieli, A. Assessment of Maize Yield and Phenology by Drone-Mounted Superspectral Camera. Precis. Agric. 2020, 21, 51–76. [Google Scholar] [CrossRef]
  114. Bauriegel, E.; Herppich, W.B. Hyperspectral and Chlorophyll Fluorescence Imaging for Early Detection of Plant Diseases, with Special Reference to Fusarium Spec. Infections on Wheat. Agriculture 2014, 4, 32–57. [Google Scholar] [CrossRef]
  115. Kuska, M.; Wahabzada, M.; Leucker, M.; Dehne, H.W.; Kersting, K.; Oerke, E.C.; Steiner, U.; Mahlein, A.K. Hyperspectral Phenotyping on the Microscopic Scale: Towards Automated Characterization of Plant-Pathogen Interactions. Plant Methods 2015, 11, 28. [Google Scholar] [CrossRef] [PubMed]
  116. Zhang, D.; Zhou, X.; Zhang, J.; Lan, Y.; Xu, C.; Liang, D. Detection of Rice Sheath Blight Using an Unmanned Aerial System with High-Resolution Color and Multispectral Imaging. PLoS ONE 2018, 13, e0187470. [Google Scholar] [CrossRef]
  117. Sun, Q.; Sun, L.; Shu, M.; Gu, X.; Yang, G.; Zhou, L. Monitoring Maize Lodging Grades via Unmanned Aerial Vehicle Multispectral Image. Plant Phenomics 2019, 2019, 5704154. [Google Scholar] [CrossRef]
  118. Khot, L.R.; Sankaran, S.; Carter, A.H.; Johnson, D.A.; Cummings, T.F. UAS Imaging-Based Decision Tools for Arid Winter Wheat and Irrigated Potato Production Management. Int. J. Remote Sens. 2016, 37, 125–137. [Google Scholar] [CrossRef]
  119. Guo, A.; Huang, W.; Dong, Y.; Ye, H.; Ma, H.; Liu, B.; Wu, W.; Ren, Y.; Ruan, C.; Geng, Y. Wheat Yellow Rust Detection Using UAV-Based Hyperspectral Technology. Remote Sens. 2021, 13, 123. [Google Scholar] [CrossRef]
  120. Shahi, T.; Xu, C.-Y.; Neupane, A.; Guo, W. Recent Advances in Crop Disease Detection Using UAV and Deep Learning Techniques. Remote Sens. 2023, 15, 2450. [Google Scholar] [CrossRef]
  121. Franceschini, M.H.D.; Bartholomeus, H.M.; Apeldoorn, D.v.; Suomalainen, J.M.; Kooistra, L. Assessing Changes in Potato Canopy Caused by Late Blight in Organic Production Systems through UAV-Based Pushbroom Imaging Spectrometer. ISPRS-Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2017, 42, 109–112. [Google Scholar] [CrossRef]
  122. Yamamoto, S.; Nomoto, S.; Hashimoto, N.; Maki, M.; Hongo, C.; Tatsuhiko, S.; Homma, K. Monitoring Spatial and Time-Series Variations in Red Crown Rot Damage of Soybean in Farmer Fields Based on UAV Remote Sensing. Plant Prod. Sci. 2023, 26, 36–47. [Google Scholar] [CrossRef]
  123. Abdulridha, J.N.; Ampatzidis, Y.; Kakarla, S.C.; Roberts, P.D. Detection of Target Spot and Bacterial Spot Diseases in Tomato Using UAV-Based and Benchtop-Based Hyperspectral Imaging Techniques. Precis. Agric. 2019, 21, 955–978. [Google Scholar] [CrossRef]
  124. Tallapragada, P.; Ross, S.D.; Schmale, D.G. Lagrangian Coherent Structures Are Associated with Fluctuations in Airborne Microbial Populations. Chaos 2011, 21, 033122. [Google Scholar] [CrossRef] [PubMed]
  125. Zhao, S.; Liu, M.; Tao, M.; Zhou, W.; Lu, X.; Xiong, Y.; Li, F.; Wang, Q. The Role of Satellite Remote Sensing in Mitigating and Adapting to Global Climate Change. Sci. Total Environ. 2023, 904, 166820. [Google Scholar] [CrossRef]
  126. Wang, J.; Long, X.; Chern, M.; Chen, X. Understanding the Molecular Mechanisms of Trade-Offs between Plant Growth and Immunity. Sci. China Life Sci. 2021, 64, 234–241. [Google Scholar] [CrossRef] [PubMed]
  127. Plett, J.M.; Plett, K.L.; Bithell, S.L.; Mitchell, C.; Moore, K.; Powell, J.R.; Anderson, I.C. Improved Phytophthora Resistance in Commercial Chickpea (Cicer arietinum) Varieties Negatively Impacts Symbiotic Gene Signalling and Symbiotic Potential in Some Varieties. Plant Cell Environ. 2016, 39, 1858–1869. [Google Scholar] [CrossRef] [PubMed]
  128. Li, Q.; Wang, B.; Yu, J.; Dou, D. Pathogen-Informed Breeding for Crop Disease Resistance. J. Integr. Plant Biol. 2021, 63, 305–311. [Google Scholar] [CrossRef] [PubMed]
  129. Hui, C.; Jiang, H.; Liu, B.; Wei, R.; Zhang, Y.; Zhang, Q.; Liang, Y.; Zhao, Y. Chitin Degradation and the Temporary Response of Bacterial Chitinolytic Communities to Chitin Amendment in Soil under Different Fertilization Regimes. Sci. Total Environ. 2020, 705, 136003. [Google Scholar] [CrossRef]
  130. Shen, Z.; Xue, C.; Penton, C.R.; Thomashow, L.S.; Zhang, N.; Wang, B.; Ruan, Y.; Li, R.; Li, R.; Shen, Q. Suppression of Banana Panama Disease Induced by Soil Microbiome Reconstruction through an Integrated Agricultural Strategy. Soil Biol. Biochem. 2019, 128, 164–174. [Google Scholar] [CrossRef]
  131. Troy, T.; Kipgen, C.; Pal, I. The Impact of Climate Extremes and Irrigation on US Crop Yields. Environ. Res. Lett. 2015, 10, 054013. [Google Scholar] [CrossRef]
  132. Wheeler, T.A.; Bordovsky, J.P.; Keeling, J.W. The Effectiveness of Crop Rotation on Management of Verticillium Wilt over Time. Crop Prot. 2019, 121, 157–162. [Google Scholar] [CrossRef]
  133. Kpu, K.A.; Annih, M.G.; Ambang, A.L.; Agwah, E.D. Influence of Tillage Systems and Sowing Dates on the Incidence of Leaf Spot Disease in Telfairia occidentalis Caused by Phoma sorghina in Cameroon. Sci. Rep. 2022, 12, 19790. [Google Scholar] [CrossRef] [PubMed]
  134. Shukla, M.; Sadhu, A.; Chinchmalatpure, A.; Prasad, I.; Kumar, S.; Camus, D. Fertigation-Modern Technique of Fertilizer Application. Indian Farmer 2018, 5, 1062–1071. [Google Scholar]
  135. Breda, C.C.; Soares, M.B.; Tavanti, R.F.R.; Viana, D.G.; Freddi, O.d.S.; Piedade, A.R.; Mahl, D.; Traballi, R.C.; Guerrini, I.A. Successive Sewage Sludge Fertilization: Recycling for Sustainable Agriculture. Waste Manag. 2020, 109, 38–50. [Google Scholar] [CrossRef]
  136. Saccon, P. Water for Agriculture, Irrigation Management. Appl. Soil Ecol. 2018, 123, 793–796. [Google Scholar] [CrossRef]
  137. Collinge, D.B.; Jørgensen, H.J.L.; Latz, M.A.C.; Manzotti, A.; Ntana, F.; Rojas, E.C.; Jensen, B. Searching for Novel Fungal Biological Control Agents for Plant Disease Control Among Endophytes. In Endophytes for a Growing World; Cambridge University Press: Cambridge, UK, 2019. [Google Scholar]
  138. Lamichhane, J.R.; Dachbrodt-Saaydeh, S.; Kudsk, P.; Messéan, A. Toward a Reduced Reliance on Conventional Pesticides in European Agriculture. Plant Dis. 2016, 100, 10–24. [Google Scholar] [CrossRef] [PubMed]
  139. Strange, R.N.; Scott, P.R. Plant Disease: A Threat to Global Food Security. Annu. Rev. Phytopathol. 2005, 43, 83–116. [Google Scholar] [CrossRef]
  140. Cooper, J.; Dobson, H.M. The Benefits of Pesticides to Mankind and the Environment. Crop Prot. 2007, 26, 1337–1348. [Google Scholar] [CrossRef]
  141. Kawasaki, K.; Lichtenberg, E. Quality Versus Quantity Effects of Pesticides: Joint Estimation of Quality Grade and Crop Yield. In Proceedings of the 2015 AAEA & WAEA Joint Annual Meeting, San Francisco, CA, USA, 26–28 July 2015. [Google Scholar]
  142. Carvalho, F. Agriculture, Pesticides, Food Security and Food Safety. Environ. Sci. Policy 2006, 9, 685–692. [Google Scholar] [CrossRef]
  143. Damalas, C.A.; Eleftherohorinos, I.G. Pesticide Exposure, Safety Issues, and Risk Assessment Indicators. Int. J. Environ. Res. Public Health 2011, 8, 1402–1419. [Google Scholar] [CrossRef] [PubMed]
  144. Kim, K.H.; Kabir, E.; Jahan, S.A. Exposure to Pesticides and the Associated Human Health Effects. Sci. Total Environ. 2017, 575, 525–535. [Google Scholar] [CrossRef] [PubMed]
  145. Li, Z.; Sun, J.; Zhu, L. Organophosphorus Pesticides in Greenhouse and Open-Field Soils across China: Distribution Characteristic, Polluted Pathway and Health Risk. Sci. Total Environ. 2021, 765, 142757. [Google Scholar] [CrossRef] [PubMed]
  146. Carro-Huerga, G.; Mayo-Prieto, S.; Rodríguez-González, Á.; González-López, Ó.; Gutiérrez, S.; Casquero, P.A. Influence of Fungicide Application and Vine Age on Trichoderma Diversity as Source of Biological Control Agents. Agronomy 2021, 11, 446. [Google Scholar] [CrossRef]
  147. Ren, B.; Zhao, T.; Li, Y.; Liang, H.; Zhao, Y.; Chen, H.; Li, L.; Liang, H. Enantioselective Bioaccumulation and Toxicity of the Novel Chiral Antifungal Agrochemical Penthiopyrad in Zebrafish (Danio rerio). Ecotoxicol. Environ. Saf. 2021, 228, 113010. [Google Scholar] [CrossRef] [PubMed]
  148. Borel, B. When the Pesticides Run Out. Nature 2017, 543, 302–304. [Google Scholar] [CrossRef] [PubMed]
  149. Bass, C.; Denholm, I.; Williamson, M.S.; Nauen, R. The Global Status of Insect Resistance to Neonicotinoid Insecticides. Pestic. Biochem. Physiol. 2015, 121, 78–87. [Google Scholar] [CrossRef] [PubMed]
  150. Price, C.L.; Parker, J.E.; Warrilow, A.; Kelly, D.E.; Kelly, S.L. Azole Fungicides—Understanding Resistance Mechanisms in Agricultural Fungal Pathogens. Pest Manag. Sci. 2015, 71, 1054–1058. [Google Scholar] [CrossRef] [PubMed]
  151. Li, L.; Xu, Z.; Kah, M.; Lin, D.; Filser, J. Nanopesticides: A Comprehensive Assessment of Environmental Risk Is Needed before Widespread Agricultural Application. Environ. Sci. Technol. 2019, 53, 7923–7924. [Google Scholar] [CrossRef] [PubMed]
  152. Wang, M.; Hu, Z.; Yang, T.; Pei, H.; Zhang, F. A Dual Pesticide–Fertilizer Silicon-Base Nanocomposite to Synergistically Control Fungal Disease and Provide Nutrition. Environ. Sci. Nano 2023, 10, 3462–3475. [Google Scholar] [CrossRef]
  153. Stenberg, J.A.; Sundh, I.; Becher, P.G.; Björkman, C.; Dubey, M.; Egan, P.A.; Friberg, H.; Gil, J.F.; Jensen, D.F.; Jonsson, M.; et al. When Is It Biological Control? A Framework of Definitions, Mechanisms, and Classifications. J. Pest Sci. 2021, 94, 665–676. [Google Scholar] [CrossRef]
  154. Veras, F.F.; Silveira, R.D.; Welke, J.E. Bacillus spp. As a Strategy to Control Fungi and Mycotoxins in Food. Curr. Opin. Food Sci. 2023, 52, 101068. [Google Scholar] [CrossRef]
  155. Glick, B.R. Bacteria with ACC Deaminase Can Promote Plant Growth and Help to Feed the World. Microbiol. Res. 2014, 169, 30–39. [Google Scholar] [CrossRef] [PubMed]
  156. Dong, W.; Long, T.; Ma, J.; Wu, N.; Mo, W.; Zhou, Z.; Jin, J.; Zhou, H.; Ding, H. Effects of Bacillus velezensis GUAL210 Control on Edible Rose Black Spot Disease and Soil Fungal Community Structure. Front. Microbiol. 2023, 14, 1199024. [Google Scholar] [CrossRef] [PubMed]
  157. Nuangmek, W.; Aiduang, W.; Kumla, J.; Lumyong, S.; Suwannarach, N. Evaluation of a Newly Identified Endophytic Fungus, Trichoderma phayaoense for Plant Growth Promotion and Biological Control of Gummy Stem Blight and Wilt of Muskmelon. Front. Microbiol. 2021, 12, 634772. [Google Scholar] [CrossRef] [PubMed]
  158. Bhavani, P.; Suganya, K.; Parwin Banu, K.S.; Ramalakshmi, A.; Nalina, L. Effects of Root Exudates of Vetiver on Physicochemical Properties and Fractionation of Heavy Metals in Tannery Effluent Contaminated Soil. Ecol. Environ. Conserv. 2023, 29, 164–169. [Google Scholar] [CrossRef]
  159. Berendsen, R.L.; Pieterse, C.M.J.; Bakker, P.A.H.M. The Rhizosphere Microbiome and Plant Health. Trends Plant Sci. 2012, 17, 478–486. [Google Scholar] [CrossRef] [PubMed]
  160. Hasegawa, S.; Ryan, M.H.; Power, S.A. CO2 Concentration and Water Availability Alter the Organic Acid Composition of Root Exudates in Native Australian Species. Plant Soil 2023, 485, 507–524. [Google Scholar] [CrossRef]
  161. Wu, J.; Yu, S. Effect of Root Exudates of Eucalyptus urophylla and Acacia mearnsii on Soil Microbes under Simulated Warming Climate Conditions. BMC Microbiol. 2019, 19, 224. [Google Scholar] [CrossRef]
  162. Climate Warming Threatens Soil Microbial Diversity. Nat. Microbiol. 2022, 7, 935–936. [CrossRef] [PubMed]
  163. Li, X.; Dong, J.; Chu, W.; Chen, Y.; Duan, Z. The Relationship between Root Exudation Properties and Root Morphological Traits of Cucumber Grown under Different Nitrogen Supplies and Atmospheric CO2 Concentrations. Plant Soil 2018, 425, 415–432. [Google Scholar] [CrossRef]
  164. Vicente, E.J.; Dean, D.R. Keeping the Nitrogen-Fixation Dream Alive. Proc. Natl. Acad. Sci. USA 2017, 114, 3009–3011. [Google Scholar] [CrossRef] [PubMed]
  165. Shah, A.; Nazari, M.; Antar, M.S.M.; Msimbira, L.A.; Naamala, J.; Lyu, D.; Rabileh, M.A.; Zajonc, J.; Smith, D.L. PGPR in Agriculture: A Sustainable Approach to Increasing Climate Change Resilience. Front. Sustain. Food Syst. 2021, 5, 667546. [Google Scholar] [CrossRef]
  166. Zytynska, S.E.; Eicher, M.; Rothballer, M.; Weisser, W.W. Microbial-Mediated Plant Growth Promotion and Pest Suppression Varies Under Climate Change. Front. Plant Sci. 2020, 11, 573578. [Google Scholar] [CrossRef] [PubMed]
  167. Berg, G.; Rybakova, D.; Fischer, D.; Cernava, T.; Vergès, M.C.; Charles, T.; Chen, X.; Cocolin, L.; Eversole, K.; Corral, G.H.; et al. Microbiome Definition Re-Visited: Old Concepts and New Challenges. Microbiome 2020, 8, 103. [Google Scholar] [CrossRef]
  168. Zhu, S.; Vivanco, J.M.; Manter, D.K. Nitrogen Fertilizer Rate Affects Root Exudation, the Rhizosphere Microbiome and Nitrogen-Use-Efficiency of Maize. Appl. Soil Ecol. 2016, 107, 324–333. [Google Scholar] [CrossRef]
  169. Zhou, X.; Zhang, J.; Khashi u Rahman, M.; Gao, D.; Wei, Z.; Wu, F.; Dini-Andreote, F. Interspecific Plant Interaction via Root Exudates Structures the Disease Suppressiveness of Rhizosphere Microbiomes. Mol. Plant 2023, 16, 849–864. [Google Scholar] [CrossRef] [PubMed]
  170. Zhou, Y.; Liu, Y.; Li, S.; Yang, Q. The Combination of Biochar and Bacillus subtilis Biological Agent Reduced the Relative Abundance of Pathogenic Bacteria in the Rhizosphere Soil of Panax notoginseng. Microorganisms 2024, 12, 783. [Google Scholar] [CrossRef] [PubMed]
  171. Chen, W.; Wu, Z.; Liu, C.; Zhang, Z.; Liu, X. Biochar Combined with Bacillus subtilis SL-44 as an Eco-Friendly Strategy to Improve Soil Fertility, Reduce Fusarium Wilt, and Promote Radish Growth. Ecotoxicol. Environ. Saf. 2023, 251, 114509. [Google Scholar] [CrossRef] [PubMed]
  172. Xiong, W.; Reynolds, M.; Xu, Y. Climate Change Challenges Plant Breeding. Curr. Opin. Plant Biol. 2022, 70, 102308. [Google Scholar] [CrossRef] [PubMed]
  173. Samada, L.H.; Tambunan, U.S.F. Biopesticides as Promising Alternatives to Chemical Pesticides: A Review of Their Current and Future Status. J. Biol. Sci. 2020, 20, 66–76. [Google Scholar] [CrossRef]
  174. Chandrika, K.S.V.P.; Prasad, R.D.; Godbole, V. Development of Chitosan-PEG Blended Films using Trichoderma: Enhancement of Antimicrobial Activity and Seed Quality. Int. J. Biol. Macromol. 2019, 126, 282–290. [Google Scholar] [CrossRef] [PubMed]
Agriculture 14 01108 g001
Figure 1. Relationship between climate, crops, and fungal pathogens.
Figure 1. Relationship between climate, crops, and fungal pathogens.
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Figure 2. Dynamic equilibrium between crop–biology–soil.
Figure 2. Dynamic equilibrium between crop–biology–soil.
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Table 1. Prevalence of crop fungal diseases due to climate change.
Table 1. Prevalence of crop fungal diseases due to climate change.
Type of Climate ChangeCropDiseasePathogenic FungusHazardReference
DesertificationFaba beanRoot rotFusarium equiseti, Fusarium graminearum, Fusarium brachygibbosumGrowth rate of pathogenic fungi increased by 30–44%[21]
ChickpeaRoot rotMacrophomina phaseolinaChickpea production down 66.99%[27]
RiceRice blastMagnaporthe oryzaePlants under drought for longer have higher fungal abundance and poorer germination[28]
Flooding and high humidityCucumberDamping-off diseasePythium aphanidermatumSignificant increase in morbidity from 40% to 93%[35]
Sugar caneFalse floral smutEpicoccum andropogonis, Claviceps purpureaHeavy precipitation during the bloom period resulted in a higher incidence than in previous years[40]
CashewLeaf blightCryptosporiopsis spp.2% increase in incidence per mm increase in rainfall[41]
QuinoaDowny mildewPeronospora variabilisDecreased chlorophyll in quinoa after disease onset[43]
High temperaturesGrapevine trunkGrapevine trunk diseaseLasiodiplodia theobromaePathogenic fungi grow at 4 °C–40 °C and prefer higher temperatures[46]
CeleryRoot rotFusarium oxysporumFusarium acanthamoeba levels and disease severity increased with increasing temperature[48]
SoybeanRoot rotFusarium solaniLonger root lesion lengths and higher disease incidence of Fusarium at 30 °C[49]
Table 2. Mechanisms by which climate change impacts fungal diseases with different transmission routes.
Table 2. Mechanisms by which climate change impacts fungal diseases with different transmission routes.
Transmission RouteCropPathogenic FungusMechanisms of InfluenceReference
Soil-borne diseaseTomatoFusarium solani, F. oxysporum or Ilyonectria destructansCrops are more susceptible to extreme summer temperatures and drought[54,57,58,59]
MaizeFusarium graminearumHigh temperatures trigger oxidative stress in grains that damages enzymes and tissues, making fungi more susceptible to infestation[61]
Air-borne diseaseCucurbitPseudoperonospora cubensisRelative humidity > 90% and temperature 15 °C–20 °C are optimal conditions for cucurbit downy mildew development[78,79]
PotatoAlternaria solaniStreptomyces levels exceed 50 spores/m3 at average temperature > 18 °C and leaf humidity > 80%[84,85]
Seed-borne diseaseWheatTilletia cariesStored seeds are affected by temperature and humidity[91]
PeanutAspergillus flavusIncrease in the proportion of Aspergillus flavus colonizing peanuts and aflatoxin concentration with increasing temperature[92]
RiceFusarium fujikuroi At >25 °C, mycelium grows most vigorously[93]
Table 3. Methods for diagnosing crop fungal diseases.
Table 3. Methods for diagnosing crop fungal diseases.
Method CategoryDiagnostic MethodPrincipleAdvantages and DisadvantagesReference
Traditional detection methodsVisual inspection methodIsolation of pathogens and interpretation of visual symptoms of disease through microscopyHighly subjective and error-prone[96]
CultureMorphological characterization of pathogens by medium culture and microscopic observationCheap, simple, but accuracy and reliability depend on experience and skill, time-consuming[97]
Modern testing methodsDirect detection methodsImmunological methodsBased on antigen–antibody bindingShort detection time, low sensitivity and accuracy[98]
Polymerase chain reaction (PCR)Detection of target nucleic acids specific to the target pathogenFast detection, lack of standardization, additional sample preparation, difficult on-site operation, high detection cost[99,100]
Indirect detection methodsspectroscopyMeasurement of the intensity of reflected light wavelengths irradiated by a specific light source to assess the health of the cropInability to detect disease prior to onset, and inability to detect multiple diseases occurring at the same time[101,102]
Biosensor detectionProvides selective quantitative or semiquantitative analytical information using biometric elementsQuantitative information on crop diseases is available, but commercially available equipment is limited[103,104]
GC–MS Assessment of changes in volatiles due to fungal infection of cropsNo crop damage, continuous monitoring over long periods of time, environmental factors interfere with sensor readings, pre-collection of samples required[105,106,107]
Imaging technologyIndirect diagnosis of diseases by detecting changes in color, texture, or temperature of crop leavesEfficient and inexpensive, suitable for climate change conditions[108,109]
Table 4. Control of crop fungal diseases under climate change.
Table 4. Control of crop fungal diseases under climate change.
Preventive and Curative MeasuresPrinciples of Prevention and TreatmentAdvantagesDisadvantagesReference
Breeding for disease resistanceTargeted selection or alteration of certain genotypes to produce new varieties of crops that are resistant to diseaseOne of the most effective and economical measuresHigh-quality resistance results in the targeted selection of pathogens[126,127,128]
Agronomic measuresFertilization, irrigation, and so on to create environmental conditions suitable for the growth and development of vegetables and the survival and reproduction of beneficial organisms, but not conducive to the occurrence of pathogenic fungiImprove the physical and chemical properties of the soil to provide a good growing environment for cropsHigh upfront costs, and labor-intensive and time-consuming process[129,130,131,134,135,136]
Chemical controlChemical pesticides kill pathogenic fungiBy far the most commonly used control methodPathogen resistance, environmental risks[137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152]
Biological controlUse of organisms such as crops, insects, and microorganisms to limit diseases caused by pathogensA green, healthy, and promising approachColonization by free microorganisms is difficult, and the preventive effect is unstable in extreme climate conditions such as drought and high temperature[153,154,155,156,157]
Ecological regulationProvide a favorable environment for healthy crop growth and maintain crop–biology–soil dynamic balanceMaintaining a dynamic crop–biology–soil balancethe complexity of its application and long time to obtain results.[158,159,160,161,162,163,164,165,166,167,168,169,170]
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Zhou, J.; Zhang, X.; Qu, Z.; Zhang, C.; Wang, F.; Gao, T.; Yao, Y.; Liang, J. Progress in Research on Prevention and Control of Crop Fungal Diseases in the Context of Climate Change. Agriculture 2024, 14, 1108. https://doi.org/10.3390/agriculture14071108

AMA Style

Zhou J, Zhang X, Qu Z, Zhang C, Wang F, Gao T, Yao Y, Liang J. Progress in Research on Prevention and Control of Crop Fungal Diseases in the Context of Climate Change. Agriculture. 2024; 14(7):1108. https://doi.org/10.3390/agriculture14071108

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Zhou, Jien, Xueyan Zhang, Zheng Qu, Chenchen Zhang, Feng Wang, Tongguo Gao, Yanpo Yao, and Junfeng Liang. 2024. "Progress in Research on Prevention and Control of Crop Fungal Diseases in the Context of Climate Change" Agriculture 14, no. 7: 1108. https://doi.org/10.3390/agriculture14071108

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