Crop Disease Control Research Articles

Characterization of a broad-spectrum antifungal strain, Streptomyces graminearus STR-1, against Magnaporthe oryzae.

Fungal diseases such as the devastating rice blast pose severe threats to crop production worldwide. Biological control of crop diseases caused by fungal pathogens is an environment-friendly approach for safeguarding crop production. But the insufficient availability of microbial agents effective against various fungal diseases has hampered the development of green production in crops. In this study, we identified a broad-spectrum antifungal bacterium, Streptomyces graminearus STR-1, showing antagonistic activity to diverse fungal pathogens including Magnaporthe oryzae, Rhizoctonia solani, Fusarium graminearum, Ustilaginoidea virens, and Bipolaris maydis. Its antifungal activity was relatively stable and less affected by temperature and pH. Evaluation of the biocontrol activity of STR-1 revealed that STR-1 prevented and controlled rice blast disease via eliciting plant immunity and suppressing fungal infection-structure development. STR-1 broth extract inhibited spore germination, likely through inhibiting protein synthesis. Combining LC-MS and chromatography analysis of the antimicrobial compounds purified from STR-1 broth extract, together with decoding STR-1 genomic sequence, we identified 4-oxo-4-[(1-phenylethyl)amino]but-2-enoic acid, 1,3,5-Trimethylpyrazole and SMA-1 as the potential main STR-1 secondary metabolites associated with its antifungal effects. This study suggests that bacterial strain STR-1 could be used for identifying highly effective and broad-spectrum secondary metabolites for containing rice blast and other crop diseases. The application of the active compounds offers a promising measure to tackle fungal disease.

Isolation of Streptomyces inhibiting multiple-phytopathogenic fungi and characterization of lucensomycin biosynthetic gene cluster

Soil microorganisms with diverse bioactive compounds such as Streptomyces are appreciated as valuable resources for the discovery of eco-friendly fungicides. This study isolated a novel Streptomyces from soil samples collected in the organic green tea fields in South Korea. The isolation process involved antifungal activity screening around 2400 culture extracts, revealing a strain designated as S. collinus Inha504 with remarkable antifungal activity against diverse phytopathogenic fungi. S. collinus Inha504 not only inhibited seven phytopathogenic fungi including Fusarium oxysporum and Aspergillus niger in bioassays and but also showed a control effect against F. oxysporum infected red pepper, strawberry, and tomato in the in vivo pot test. Genome mining of S. collinus Inha504 revealed the presence of the biosynthetic gene cluster (BGC) in the chromosome encoding a polyene macrolide which is highly homologous to the lucensomycin (LCM), a compound known for effective in crop disease control. Through genetic confirmation and bioassays, the antifungal activity of S. collinus Inha504 was attributed to the presence of LCM BGC in the chromosome. These results could serve as an effective strategy to select novel Streptomyces strains with valuable biological activity through bioassay-based screening and identify biosynthetic gene clusters responsible for the metabolites using genome mining approach.

Smallholder farmers’ perceived motivations for the adoption and implementation of climate information services in the Atwima Nwabiagya District, Ghana

This study investigated smallholder farmers’ perceived motivations for the adoption and implementation of climate information services (CIS) in the Atwima Nwabiagya District, Ghana. Specifically, the study answered the following research questions. (i) What is the perception of smallholder farmers on climate change and variability in the Atwima Nwabiagya District?; (ii) What are the CIS accessed and used by the smallholder farmers for farm management decisions?; (iii) What are the perceived motivations for the adoption and implementation of CIS by smallholder farmers?; and; (iv) What are the barriers confronting smallholder farmers in adopting and implementing CIS? Primary data was collected through questionnaire surveys with 200 farming households and four key informant interviews in four selected communities (Kobeng, Seidi, Wioso, and Nkawie Panin) in the study district. Results showed that smallholder farmers perceived climate change and variability through increased windstorms and thunderstorms, variable rainfall, and increased temperature patterns. The surveyed farmers also perceived that the climatic changes affect their agricultural activities adversely. However, the smallholder farmers accessed and used CIS including weather warnings (86%), daily weather forecasts (70%), and seasonal forecasts (60%) to manage climatic risks on the farm. Results also showed that the smallholder farmers were motivated by critical factors including improvement in the acquisition of proactive measures (92%), increased knowledge of climatic patterns that affect food stock (91%), and a reduction in loss of stock produced (88%) to access and use CIS. Despite this, the smallholder farmers were confronted with key barriers in their uptake and utilization of CIS. These were the timeliness of CIS (73%), a lack of weather symbols in the forecasts (65%), and inadequate information on seasonal forecasts for long-term planning (61%). The study concluded that the motivations for smallholder farmers using CIS in the study district may vary depending on their context, goals, and challenges. However, the general motivation is to enhance smallholder farmers’ farm planning and risk management by using weather and climate forecasts to make better decisions on crop selection, planting dates, input use, pest and disease control, irrigation, harvesting, and marketing.

The activity of leaf extracts, fractions, and isolated compounds from Ptaeroxylon obliquum against nine phytopathogenic fungi and the nematode Meloidogyne incognita

Phytopathogenic fungi and nematodes cause great losses in economically important crops and food production especially in developing countries. To minimize the use of fungicides and nematicides, researchers have concentrated on the use of natural products for crop disease prevention or control. The aim of the study was to investigate the antifungal activity of Ptaeroxylon obliquum leaf extracts, fractions, and isolated compounds (obliquumol and a mixture of lupeol and β-amyrin) and nematocidal activity of fractions (hexane, chloroform and 30% water in methanol and the isolated compounds) on Meloidogyne incognita. Nine phytopathogenic fungi (Aspergillus niger, A. parasiticus, Colletotrichum gloeosporioides, Fusarium oxysporum, Penicillium digitatum, P. expansum, P. italicum, P. janthinellum, and Rhizoctonia solani) were used for testing and nematocidal activity was determined on motility of plant parasitic nematode Meloidogyne incognita race 2 juveniles. Serial microdilution test was utilized to determine the minimum inhibitory concentration (MIC) of each sample against the fungus. Motility tests was done on the second-stage juveniles (J2s) of M. incognita. The most susceptible phytopathogenic fungal species to the acetone crude leaf extracts were A. niger, C. gloeosporioides and P. digitatum with MIC of 80 μg/ml which is considered pharmacological significant. Rhizoctonia solani was the most susceptible fungus against obliquumol and, lupeol and β-amyrin mixture with MIC values of 8 μg/ml and 16 μg/ml respectively. Lupeol & β-amyrin mixture had good activity on juvenile motility at high concentrations used which was significantly high (p ≤ 0.05) after 24 h, further incubation resulted in temporary paralysis at lower concentrations. Fractions and obliquumol showed good activity after 48 h, stable paralysis was observed up to 72 h. The extracts and isolated compounds may be useful as fungicides if the in vitro results can be confirmed under field conditions at levels not toxic to beneficial soil organisms.

Identifying the suite of genes central to swimming in the biocontrol bacterium Pseudomonas protegens Pf-5.

Swimming motility is a key bacterial trait, important to success in many niches. Biocontrol bacteria, such as Pseudomonas protegens Pf-5, are increasingly used in agriculture to control crop diseases, where motility is important for colonization of the plant rhizosphere. Swimming motility typically involves a suite of flagella and chemotaxis genes, but the specific gene set employed for both regulation and biogenesis can differ substantially between organisms. Here we used transposon-directed insertion site sequencing (TraDIS), a genome-wide approach, to identify 249 genes involved in P. protegens Pf-5 swimming motility. In addition to the expected flagella and chemotaxis, we also identified a suite of additional genes important for swimming, including genes related to peptidoglycan turnover, O-antigen biosynthesis, cell division, signal transduction, c-di-GMP turnover and phosphate transport, and 27 conserved hypothetical proteins. Gene knockout mutants and TraDIS data suggest that defects in the Pst phosphate transport system lead to enhanced swimming motility. Overall, this study expands our knowledge of pseudomonad motility and highlights the utility of a TraDIS-based approach for analysing the functions of thousands of genes. This work sets a foundation for understanding how swimming motility may be related to the inconsistency in biocontrol bacteria performance in the field.

Using a Hybrid Convolutional Neural Network with a Transformer Model for Tomato Leaf Disease Detection

Diseases of tomato leaves can seriously damage crop yield and financial rewards. The timely and accurate detection of tomato diseases is a major challenge in agriculture. Hence, the early and accurate diagnosis of tomato diseases is crucial. The emergence of deep learning has dramatically helped in plant disease detection. However, the accuracy of deep learning models largely depends on the quantity and quality of training data. To solve the inter-class imbalance problem and improve the generalization ability of the classification model, this paper proposes a cycle-consistent generative-adversarial-network-based Transformer model to generate diseased tomato leaf images for data augmentation. In addition, this paper uses a Transformer model and densely connected CNN architecture to extract multilevel local features. The Transformer module is utilized to capture global dependencies and contextual information accurately to expand the sensory field of the model. Experiments show that the proposed model achieved 99.45% accuracy on the PlantVillage dataset. The 2018 Artificial Intelligence Challenger dataset and the private dataset attained accuracies of 98.30% and 95.4%, and the proposed classification model achieved a higher accuracy and smaller model size compared to previous deep learning models. The classification model is generalizable and robust and can provide a stable theoretical framework for crop disease prevention and control.

Deep Learning Techniques for Identification of Different Malvaceae Plant Leaf Diseases

INTRODUCTION: The precise and timely detection of plant diseases plays a crucial role in ensuring efficient crop management and disease control. Nevertheless, conventional methods of disease identification, which heavily rely on manual visual inspection, are often time-consuming and susceptible to human error. The knowledge acquired from this research paper enhances the overall comprehension of the discipline and offers valuable direction for future progressions in the application of deep learning for the identification of plant diseases.[1][2] AIM: to investigate the utilization of deep learning techniques in identifying various Malvaceae plant diseases. METHODS: AlexNet, VGG, Inception, REsNet and other CNN architectures are analyzed on Malvaceae plant diseases specially on Cotton, Ocra and Hibiscus, different data collection methods ,Data augmentation and Normalization techniques. RESULTS: Inception V4 have Training Accuracy 98.58%, VGG-16 have Training Accuracy 84.27%, ResNet-50 have Training Accuracy 98.72%, DenseNet have Training Accuracy 98.87%, Inception V4 have Training Loss 0.01%, VGG-16 have Training Loss 0.52%, ResNet-50 have Training Loss 6.12%, DenseNet have Training Loss 0.016%, Inception V4 have Test Accuracy 97.59%, VGG-16 have Test accuracy 82.75%, ResNet-50 have Test Accuracy 98.73%, DenseNet have Test Accuracy 99.81%, Inception V4 have Test Loss 0.0586%, VGG-16 have Test Loss 0.64%, ResNet-50 have Test Loss 0.027%, DenseNet have Test Loss 0.0154% . CONCLUSION: conclusion summarizes the key findings and highlights the potential of deep learning as a valuable tool for accurate and efficient identification of Malvaceae plant diseases.

G-C3N4@CuO electrostatic self-assembly toward Ralstonia solanacearum: Insights from cytomembrane and motility disruption.

Ralstonia solanacearum, a notorious and refractory bacterial plant pathogen, threatens multiple vegetable crops and causes significant economic loss in agriculture. Long-term use of traditional medicines not only increases the problem of drug resistance, but also causes great environmental pollution. Therefore, there is an urgent need to develop new agents with high efficacy and low toxicity. In this study, we have synthesized and characterized graphitic carbon nitride incorporated copper oxide composite (g-C3N4@CuO), which showed higher antimicrobial effect than graphitic carbon nitride nanosheets (g-C3N4 nanosheets) and copper oxide nanoparticles (CuONPs). Ralstonia solanacearum exposed to g-C3N4@CuO exhibited higher levels of oxygen toxicity, cell membrane damage, DNA damage, motility disruption and even cell death compared to g-C3N4 nanosheets and CuONPs. In addition, g-C3N4@CuO was more effective in the control of tobacco bacterial wilt than g-C3N4 nanosheets and CuONPs. Thus, this study provides a new perspective on g-C3N4@CuO control of bacterial diseases in crops, and the mechanism is related to the destruction of cell membrane damage and motility disruption. © 2024 Society of Chemical Industry.

Septin-dependent invasive growth by the rice blast fungus Magnaporthe oryzae

Septin GTPases are morphogenetic proteins that are widely conserved in eukaryotic organisms fulfilling diverse roles in cell division, differentiation and development. In the filamentous fungal pathogen Magnaporthe oryzae, the causal agent of the devastating blast diseases of rice and wheat, septins have been shown to be essential for plant infection. The blast fungus elaborates a specialised infection structure called an appressorium with which it mechanically ruptures the plant cuticle. Septin aggregation and generation of a hetero-oligomeric ring structure at the base of the infection cell is indispensable for plant infection. Furthermore, once the fungus enters host tissue it develops another infection structure, the transpressorium, enabling it to move between living host plant cells, which also requires septins for its function. Specific inhibition of septin aggregation—either genetically or with chemical inhibitors—prevents plant infection. Significantly, by screening for inhibitors of septin aggregation, broad spectrum anti-fungal compounds have been identified that prevent rice blast and a number of other cereal diseases in field trials. We review the recent advances in our understanding of septin biology and their potential as targets for crop disease control.

Microbial Biofungicides as a Substitute for Chemical Fungicides in the Control of Phytopathogens: Current Perspectives and Research Directions.

These days, two important issues are causing concern in the global community: the alarmingly growing trend of the human population and the issue of food security. To this end, people around the world have been searching for solutions that could feed the needy in a sustainable way. In response to this urgent call, scientists from around the world started working on increasing crop production and productivity by controlling crop pathogens that could harm the productivity of crops. Synthetic fungicides have been in use for controlling crop diseases for several decades, but later, due to the evidenced side effects of the fungicides, there have been attempts to shift towards a less cost-effective and eco-friendly method of controlling crop diseases, and so far, many remarkable results have been achieved. However, due to the less effective and shorter shelf life of microbial biofungicides, as well as the less accessibility of these microbial biofungicides to growers around the world, it became difficult to remove the fungicides totally from the market. To minimize this problem, researchers suggested an integrated approach: the combination of microbial biofungicides with a reduced dose of synthetic fungicides. Hence, this review explored the status as well as the merits and demerits of microbial biofungicides as compared to synthetic fungicides.

Perception of the Biocontrol Potential and Palmitic Acid Biosynthesis Pathway of Bacillus subtilis H2 through Merging Genome Mining with Chemical Analysis.

Bacillus has been widely studied for its potential to protect plants from pathogens. Here, we report the whole genome sequence of Bacillus subtilis H2, which was isolated from the tea garden soil of Guiyang Forest Park. Strain H2 showed a broad spectrum of antagonistic activities against many plant fungal pathogens and bacteria pathogens, including the rice blast fungus Magnaporthe oryzae, and showed a good field control effect against rice blast. The complete genome of B. subtilis H2 contained a 4,160,635-bp circular chromosome, with an average G + C content of 43.78%. Through the genome mining of strain H2, we identified 7 known antimicrobial compound biosynthetic gene clusters (BGCs) including sporulation killing factor, surfactin, bacillaene, fengycin, bacillibactin, subtilosin A, and bacilysin. Palmitic acid (PA), a secondary metabolite, was detected and identified in the H2 strain through genome mining analysis and gas chromatography-mass spectrometry (GC-MS). Additionally, we propose, for the first time, that the type II fatty acid synthesis (FAS) pathway in Bacillus is responsible for PA biosynthesis. This finding was confirmed by studying the antimicrobial activity of PA and conducting reverse transcription-quantitative polymerase chain reaction (RT-qPCR) experiments. We also identified numerous genes associated with plant-bacteria interactions in the H2 genome, including more than 94 colonization-related genes, more than 34 antimicrobial genes, and more than 13 plant growth-promoting genes. These findings contribute to our understanding of the biocontrol mechanisms of B. subtilis H2 and have potential applications in crop disease control.

Morpho-physio-biochemical, molecular, and phytoremedial responses of plants to red, blue, and green light: a review.

Light is a basic requirement to drive carbon metabolism in plants and supports life on earth. Spectral quality greatly affects plant morphology, physiology, and metabolism of various biochemical pathways. Among visible light spectrum, red, blue, and green light wavelengths affect several mechanisms to contribute in plant growth and productivity. In addition, supplementation of red, blue, or green light with other wavelengths showed vivid effects on the plant biology. However, response of plants differs in different species and growing conditions. This review article provides a detailed view and interpretation of existing knowledge and clarifies underlying mechanisms that how red, blue, and green light spectra affect plant morpho-physiological, biochemical, and molecular parameters to make a significant contribution towards improved crop production, fruit quality, disease control, phytoremediation potential, and resource use efficiency.

Design, Synthesis, and Biological Activities of Novel Coumarin Derivatives as Pesticide Candidates.

Food security is an important issue in the 21st century; preventing and controlling crop diseases and pests are the key to solve this problem. The creation of new pesticides based on natural products is an important and effective method. Herein, coumarins were selected as parent structures, and a series of their derivatives were designed, synthesized, and evaluated for their antiviral activities, fungicidal activities, and insecticidal activities. We found that coumarin derivatives exhibited good to excellent antiviral activities against tobacco mosaic virus (TMV). The antiviral activities of I-1, I-2a, I-4b, II-2c, II-2g, II-3, and II-3b are better than that of ribavirin at 500 μg/mL. Molecular docking research showed that these compounds had a strong interaction with TMV CP. These compounds also showed broad-spectrum fungicidal activities against 14 plant pathogenic fungi. The EC50 values of I-1, I-2a, I-3c, and II-2d are in the range of 1.56-8.65 μg/mL against Rhizoctonia cerealis, Physalospora piricola, Sclerotinia sclerotiorum, and Pyricularia grisea. Most of the compounds also displayed good insecticidal activities against Mythimna separata. Pesticide-likeness analysis showed that these compounds are following pesticide-likeness and have the potential to be developed as pesticide candidates. The present work lays a foundation for the discovery of novel pesticide lead compounds based on coumarin derivatives.

IoT-based system of prevention and control for crop diseases and insect pests.

Environmentally friendly technologies for the prevention and control of crop diseases and insect pests are important to reduce the use of chemical pesticides, improve the quality of agricultural products, protect the environment, and promote sustainable development of crop production. On the basis of Internet of Things (IoT) technology, we developed a prevention and control system for crop diseases and insect pests with two main components: a plant protection device (the hardware) and an information management system (the software). To be suitable for both facility- and field-based production scenarios, we incorporated two types of plant protection devices, utilizing ozone sterilization and light-trap technologies. The devices were equipped with various sensors to realize real-time collection and monitoring of data on the crop production environment. The information management system has an IoT-based architecture and includes a mobile device app to enable remote control of the plant protection devices for intelligent management of plant protection data. The system can achieve efficient management of large-scale equipment applications and multi-device collaborative work to prevent and control pests and diseases. The developed system has operated successfully for several years in China and has been applied to cucumber, tomato, rice, and other crops. We demonstrate the effectiveness and practicality of the system in a greenhouse facility and in the field.

Low swelling Alginate/Lignin network gels with redox responsiveness for sustained release of agricultural fungicide and Pb2+ complexation

Fungicides are among the most essential agrochemicals for controlling crop diseases. However, the increased consumption of fungicides has resulted in environmental pollution and adversely affected human health. The slow-release technology can improve the efficacy and reduce the required amount of fungicide. Here, we developed a low-swelling redox-responsive alginate/lignin network bearing covalently conjugated fungicide thymol-Cl. Natural reductants in the environment caused the selective cleavage of disulfide bonds and release of thymol-Cl and thiazolidin-2-one (a by-product), which both could inhibit the phytopathogenic fungus (F. oxysporum). At the same time, metal chelating groups in the gel endow strong interactions with heavy metal ions for improving soil remediation and preventing the adsorption of toxic metals by the plant roots. The fungicide-loaded carrier could alleviate the poisonous effect of fungi on maize seeds. Indeed, the secretion of natural reducing agents by fungi and maize led to the cleavage of disulfide bonds and the release of fungicides.

Utilization of Stenotrophomonas koreensis and Bacillus amyloliquefaciens for Improving Growth, Reducing Nitrogen Fertilization and Controlling Bipolaris sorokiniana in Wheat

Wheat (<em>Triticum aestivum</em> L.), a vital cereal, faces significant challenges from common root rot and spot blotch diseases caused by <em>Bipolaris sorokiniana</em>. This study aimed to explore the potential of plant growth promoting rhizobacteria (PGPR) to enhance wheat growth, reduce fertilizer input, and combat <em>Bipolaris </em>diseases. Two PGPR isolates, selected for their superior antagonistic properties, were identified as <em>Stenotrophomonas koreensis</em> RB11 and <em>Bacillus amyloliquefaciens </em>RB12. These PGPR strains displayed multiple plant growth promoting and biocontrol attributes, including phosphate solubilization, indole-3-acetic acid production, nitrogen fixation and antagonism against <em>B. sorokiniana</em> and other fungi. Wheat seed priming with the PGPR significantly improved germination, plant growth, nutrient content and biomass carbon accumulation in the rhizosphere soil. Importantly, the application of RB11 and RB12 allowed for a 25% and 50% reduction in nitrogen fertilizer usage, respectively, without compromising the yield. RB11 and RB12 also demonstrated potent inhibitory effects on <em>B. sorokiniana</em> conidial germination and significantly controlled common root rot and spot blotch in wheat, similar to those observed with the fungicide Protaf 250EC. Overall, this study underscores the multifaceted roles of <em>S. koreensis</em> RB11 and <em>B. amyloliquefaciens</em> RB12 in promoting wheat growth, reducing fertilizer inputs and effectively suppressing wheat pathogens. These findings contribute to the development of PGPR-based strategies for sustainable crop production and disease control.

Iron oxide nanoparticles as enhancers of growth-promoting bacteria: a step towards developing nano-biofertilizers

Co-inoculation of IONPs and PGPB in the soybean seed treatment improves the seedling development of soybean and shows a viable alternative for use as a nano-biofertilizer or for improving the potential control of plant diseases in crops.

Weeds and ruderal plants as potential sources of inoculum for vegetable diseases in northern Sinaloa

Weeds and ruderal plants of the families Cucurbitaceae and Solanaceae are addressed as potential sources of inoculum for the development of viral diseases such as Tomato apex necrosis virus (ToANV), zucchini (Zucchini yellow mosaic virus (ZYMV), Watermelon mosaic virus (WMV), Papaya ring spot virus (PRSV-W) and Cucumber mosaic virus (CMV). Reference is made to weeds and ruderal plants as potential sources of inoculum, including wild sunflower for powdery mildew (Golovinomyces spadiceus), wild tobacco for foliar blight (Alternaria spp.), black nightshade for leaf spot (Curvularia moehlemvekiae), Johnson grass for foliar blight (Alternaria sp.), and wild castor bean for foliar blight (Alternaria ricini) and wild melon for downy mildew (Pseudoperonospora cubensis). Future lines of multidisciplinary research focusing on the determination of pathogenicity in cultivated plants of viruses and fungi associated with wild plants and vice versa are proposed; the spatial-temporal distribution of wild plants that may serve as sources of inoculum, as well as the of potential insect vectors of viral diseases, should also be studied. The implementation of modern molecular techniques, such as High Throughput Sequencing, for the detection of phytopathogens is important. All this will contribute to the implementation of environmentally friendly strategies for disease control in agricultural crops in Sinaloa, for the benefit of the vegetable growers.

Smart Farming (Ai-Generated) as an Approach to Better Control Pest and Disease Detection in Agriculture: POV Agricultural Institutions

Purpose – The purpose of current study was to examine the role of smart farming through artificial intelligence (AI) (Data Integration; Machine Learning; Sensor Technologies; Image Processing and Computer Vision; Decision Support Systems and Scalability and Adaptability) in controlling pest and disease detection in agriculture.
 Methodology/ Design / Approach – Quantitative methodology was adopted and a questionnaire was self-administered online by (328) agricultural engineers working in private agricultural institutions in Jordan that are subject to the laws of the Jordanian Ministry of Agriculture. SPSS was employed in order to screen and analyze primary data.
 Findings – Study results indicated that acceptance of the main hypothesis that argued, “Smart Farming Agriculture has an effect on Control Pest and Disease Detection”. Results indicated an R-value (0.963) and an overall variance of 92.7%. In addition to that, among the chosen sub-variables of study, results revealed that scalability and adaptability scored that highest influence on disease detection and control with (r = 0.961) and an overall variance of 92.4%. Study recommended the necessity of training and qualifying agricultural staff to use modern agricultural technology and artificial intelligence.
 Originality – The originality of the current study lies in its application within the Jordanian environment. In addition, there weren’t direct studies that took into perspective the idea of smart farming through AI and its uses in pests and disease detection and control in crops. 
 Implications – The implications of current study stems from its ability to present the AI potentials to enhance food production, increase the efficiency of agricultural materials that would be a source in guaranteeing food security, and create job opportunities for individuals in this sector.

Green Synthesis of Zinc Oxide Nanoparticles using Eucalyptus Lanceolata Leaf Litter in the Control of Bacterial and Fungal Crop Diseases

Nanotechnology is a significant area of scientific inquiry that has garnered considerable attention from scholars in the contemporary period. Various plant materials are being explored as potential resources in green chemistry-based techniques for producing metal Nanoparticles (NPs). This is in response to the adverse impacts of synthetic chemicals, which contribute to significant abiotic climate change concerns in modern agriculture. The primary categories of crop diseases are those resulting from bacterial and fungal infestations. Once a plant becomes infected, it can pose a significant danger to the growth of crops, resulting in a decrease in yield and quality. Furthermore, such infections can adversely affect food safety, creating a health concern for humans. This work aimed to investigate the process of Green Synthesis and Characterisation of Zinc Oxide Nanoparticles (GSC-ZnO-NP) utilizing an extract derived from Eucalyptus lanceolatus (specifically, leaf litter). The paper intended to control bacterial and fungal crop diseases using the GSC-ZnO-NP in conjunction with Eucalyptus lanceolatus extracts. The sample's crystalline structure and surface characteristics have been evaluated using X-ray Diffraction (XRD) and Scanning Electron Microscopy (SEM). The antimicrobial activity of the proposed GSC-ZnO-NP was evaluated against bacterial and fungal isolates from infected crops. The progressive augmentation in magnitude ranging from 10° to 30° in XRD signifies the emergence of ZnO-NPs characterized by distinct and well-defined crystalline configurations. Also, the antimicrobial efficacy of the Zn-NPs extract was comparable to or surpassed that of Fluconazole, suggesting the prospective use of this environmentally-friendly manufactured nanomaterial as a substitute or adjunct therapy for bacterial and fungal infections caused by these microorganisms in crops.