Biotechnological Revolution in Agrifood Systems: Multidisciplinary Approaches for the Diagnosis, Management, and Epidemiology of Plant Diseases

1. Introduction

Agrifood systems have been disrupted for centuries across the globe by a plethora of plant pathogens such as bacteria, viruses, and fungi [1]. According to the most recent FAO report, plant pests and diseases are responsible for up to 40% of food losses, costing approximately USD 220 billion per year in direct and indirect expenses [2]. In this context, it has become imperative for agricultural stakeholders to adopt and promote efficient mitigation measures to ensure food security and safety [1,2]. To achieve that, three key pillars are of paramount importance to drive progress in plant disease management: diagnostics, biotechnology, and epidemiology. Early and precise detection of phytopathogens is essential for timely interventions [3], biotechnological innovations offer targeted, sustainable alternatives to potentially harmful pesticides [4,5,6], and the understanding of pathogen biology and dissemination through epidemiology ties these efforts together [7,8,9,10], ensuring effective, holistic solutions, combining several action mechanisms to minimize pathogen proliferation, reduce the chances of resistance development, and surpass health and environmental drawbacks associated with chemical pesticides.

With this in mind, the Special Issue (SI) The Diagnosis, Management, and Epidemiology of Plant Diseases invited researchers to submit works in these fields to showcase innovative multidisciplinary diagnostics, management, and epidemiological strategies, highlighting their contribution to reaching the goal of sustainable agriculture that can ensure food security worldwide.

2. Overview of Published Articles

2.1. Diagnosis

On the topic of diagnosis, the SI received three contributions. First, Kumar et al. (contribution 1) applied high-throughput sequencing (HTS) and quantitative PCR (qPCR) for virus detection in tomato cultivars (Solanum lycopersicum L.) in southern United States, namely tomato yellow leaf curl virus (TYLCV) and tomato chlorosis virus (ToCV). The researchers concluded that the complex association of these two viruses in tomato plants resulted in a higher viral load and the development of more severe disease compared to single infections. Therefore, this mixed infection may enhance the long-term resistance breakdown in commercial tomato plants holding the Ty-1 or Ty-3 and Ty-6 genes, leading to decreased fruit quality and marketable yields. Similarly, He et al. (contribution 2) used traditional diagnostic methods to identify the fungus affecting Ficus hirta plantations in China. For this purpose, the authors employed fungal culturing and morphological observations, alongside internal transcribed spacer sequencing (ITS) and pathogenicity testing, to confirm Lasiodiplodia pseudotheobromae as the causal agent. The additional biological characterization and fungicide sensitivity testing provided by the authors leveraged important information for the development of effective management and control measures for this disease.

In addition to the effective use of laboratory-based diagnostics methods, extensive research has been conducted to develop innovative diagnostic tools capable of on-field use. In this context, Djalovic et al. (contribution 3) described a machine-learning algorithm to study the effect of biotic stress caused by the bacterium Candidatus Phytoplasma solani. Particularly, an artificial neural network (ANN) was constructed based on the biochemical changes induced by the infection in peony (Paeonia tenuifolia L.), mint (Mentha × piperita L.), and dill (Anethum graveolens L.). The ANN model showed a remarkable ability in distinguishing between asymptomatic and symptomatic plants as demonstrated by the high coefficient of determination and low Sum of Squares. Taking advantage of computational methodologies, machine learning algorithms will be implemented directly on-field to develop an effective early warning system to improve crop yield and quality.

2.2. Management

The sustainable management of plant diseases topic received four contributions. Here, Montoya-Martínez et al. (contribution 4) evidenced the potential of Bacillus cabrialesii subsp. tritici TSO2^T to control Fusarium languescens affecting Jalapeño cultivations. After the identification of the BCA’s abilities in dual-culture assays, the authors sequenced its genome to identify the action mechanism behind them. They were able to identify gene clusters associated with biocontrol, namely related to the production of the antimicrobial metabolites, surfactins and fengycines. With a similar approach, Valenzuela-Aragon et al. (contribution 5) identified Bacillus cabrialesii subsp. cabrialesii PE1 as a potential BCA of Fusarium-related diseases in potatoes. This work validated the ability of this strain to produce antimicrobial metabolites through the testing of PE1’s liquid extract against F. languescens in vitro and through genome mining. In addition to the biosynthetic gene clusters associated with biocontrol, the authors identified coding DNA sequences related to siderophore production, which could help to decrease the accessibility of iron to phytopathogenic microorganisms in the soil (contribution 5).

Viral infections are often managed through the application of insecticides to control the vector whiteflies, with high costs to the farmers and the environment. The utilization of resistant varieties is a powerful tool to effectively manage infections and at the same time reduce the need for pesticides. Kavalappara et al. (2024) explored the Cucurbita pepo germplasm to identify resistant genotypes to the cucurbit chlorotic yellows virus (CCYV). The authors identified six potentially resistant squash accessions, among which PI420328 and PI458731 showed promise, with milder symptoms and lower viral titer after infection. The authors also point out the differences in inoculation methods to assess resistance (contribution 6).

Finally, Cerezo et al. (contribution 7) showed the potential of plant-based solutions to replace chemical pesticides as control measures against phytopathogens. Contrarily to conventional chemicals, natural plant-based preparations are considered safe, biodegradable, broad-spectrum products with low risk of resistance and toxicity development. In the article submitted to this SI, the authors explored the potential of nettle (Urtica dioica) infusions as a protection measure against the halo blight disease of common bean, caused by Pseudomonas syringae pv. phaseolicola. Results showed that pretreating common bean plants with nettle infusions significantly alleviated the symptoms of halo blight disease. This effect was attributed to the infusions’ non-enzymatic antioxidant properties, which hampered pathogen spread and consequent oxidative damage to the plant’s tissues with no detrimental effects on plant development.

2.3. Epidemiology

Lastly, two contributions were made to the SI on the epidemiology topic. Zhang et al. (contribution 8) presented a study on the virome of pimple-shaped ‘Yali’ pears. Here, the authors applied molecular techniques to analyze the virome. This was finalized by a phylogenetic tree constructed based on the amino acid sequences of the movement proteins of 6 apple stem grooving virus (ASGV) isolates and 44 ASGVs from the NCBI database. The results of this study disclosed that hosts could influence the genetic diversity of ASGV, which ultimately served as the basis for inferring the epidemiology of this virus. Besides that, the authors disclosed the presence of apple stem pitting virus (ASPV) in ‘Yali’ pear fruits for the first time. Then, the work of Cabral et al. (contribution 9) focused on the olive anthracnose caused by Colletotrichum spp. in Portugal. The authors employed surveillance efforts over two years in 525 olive groves, and a multi-locus sequencing approach on 212 isolates to confirm the presence of seven Colletotrichum species. This revealed C. alienum and C. cigarro as causal agents of olive anthracnose in Portugal for the first time, alongside the already known C. nymphaeae, C. godetiae, and C. acutatum, the first being the prevalent species and the latter expanding its geographic distribution in the country.

2.4. Reviews

The SI received review papers as well. Review articles are essential as they synthesize and consolidate knowledge from diverse sources, providing a comprehensive overview that often bridges multiple facets or disciplines (e.g., diagnosis, management, and epidemiology) within a subject and, thus, could belong to any of the sections above. In that sense, Villar-Luna et al. (contribution 10) focused on the impact of citrus greening disease (also known as Huanglongbing) caused by the plant pathogenic Candidatus Liberibacter spp. on Mexican citrus production. This review not only discloses the epidemiology of this pathogen but also reveals its negative impact on Mexican citrus production, exacerbated by inefficient management practices. It also presents the management strategies of this disease being employed in Mexico, from phytosanitary surveillance to the application of insecticides and silver nanoparticles (AgNPs) to control the insect vector and the pathogen, respectively. Lastly, a comprehensive review of Erwinia amylovora ecology, epidemiology, and sustainable control was provided by Mendes et al. (contribution 11). In this review, the authors detail the distribution pattern of this pathogen, since its first known detection in North America, and its subsequent dissemination into New Zealand, Europe, and several countries of the Asian and African continents. The polyphasic techniques employed to achieve that and to characterize the different strains are also presented in the review. Additionally, it discusses the current sustainable mitigation methods, namely, the exploration of antagonists, bacteriophages, essential oils, and antimicrobial peptides.

3. Final Remarks

These contributions emphasize the critical importance of diagnostics, sustainable compounds, and epidemiological tracking in developing new management strategies to control phytopathogens that endanger productivity in agrifood systems worldwide. Future mitigation technologies, ranging from traditional field and laboratory methods to advanced machine learning algorithms, biological control, and high-throughput detection will be integral to developing an effective management of phytopathogens. Similarly, the transformative potential of biotechnological approaches is pivotal to reducing dependency on chemical pesticides and promoting greener agriculture. Altogether, the works published within the SI entitled “The Diagnosis, Management, and Epidemiology of Plant Diseases” represent positive steps towards these goals.