Global Food Security Research Articles

Applications of Molecular Marker Implementation for Enhanced Oilseed Breeding through Marker-Assisted Selection (Mas)

Oilseed crops are fundamental for various industrial and food purposes, necessitating advancements in breeding strategies to meet growing demands. Molecular markers and Marker-Assisted Selection (MAS) have emerged as powerful tools in oilseed crop improvement. This review explores the diverse applications of molecular markers and MAS in oilseed crops, highlighting their significance in enhancing breeding efficiency and genetic gains. The primary aim of this review is to provide a comprehensive overview of the application of molecular markers and MAS in oilseed crop breeding programs. Specifically, it aims to synthesize existing literature and case studies to elucidate the methodologies, advancements, and outcomes associated with the integration of molecular markers and MAS in oilseed crop improvement. The review highlights significant advancements in the application of molecular markers and MAS in oilseed crop breeding. Molecular markers have been extensively utilized for trait mapping, genetic diversity analysis, and selection of desirable genotypes with traits such as high oil content, disease resistance, and abiotic stress tolerance. Integration with conventional breeding methods has facilitated the development of elite oilseed crop varieties with improved agronomic performance and stress resilience. In conclusion, molecular markers and MAS represent valuable tools for accelerating oilseed crop breeding programs. Their integration has led to increased breeding efficiency, precision, and genetic gains. However, challenges such as marker validation, cost-effectiveness, and trait complexity remain to be addressed. Future research efforts should focus on refining marker technologies, enhancing trait mapping studies, and promoting the adoption of MAS in oilseed crop breeding to ensure sustainable production and global food security.

QTLs and Genes for Salt Stress Tolerance: A Journey from Seed to Seed Continued

Rice (Oryza sativa L.) is a crucial crop contributing to global food security; however, its production is susceptible to salinity, a significant abiotic stressor that negatively impacts plant germination, vigour, and yield, degrading crop production. Due to the presence of exchangeable sodium ions (Na+), the affected plants sustain two-way damage resulting in initial osmotic stress and subsequent ion toxicity in the plants, which alters the cell’s ionic homeostasis and physiological status. To adapt to salt stress, plants sense and transfer osmotic and ionic signals into their respective cells, which results in alterations of their cellular properties. No specific Na+ sensor or receptor has been identified in plants for salt stress other than the SOS pathway. Increasing productivity under salt-affected soils necessitates conventional breeding supplemented with biotechnological interventions. However, knowledge of the genetic basis of salinity stress tolerance in the breeding pool is somewhat limited because of the complicated architecture of salinity stress tolerance, which needs to be expanded to create salt-tolerant variants with better adaptability. A comprehensive study that emphasizes the QTLs, genes and governing mechanisms for salt stress tolerance is discussed in the present study for future research in crop improvement.

Transforming Agriculture through Artificial Intelligence: Advancements in Plant Disease Detection, Applications, and Challenges

Artificial intelligence (AI) has emerged as a revolutionary tool in agriculture, particularly in the realm of plant disease detection. This article provides an overview of AI-powered plant disease detection methods, their applications, and the limitations associated with their implementation. By leveraging AI, farmers can enhance crop management practices, optimize resource utilization, and mitigate yield losses caused by plant diseases. However, challenges such as data scarcity, model interpretability, and deployment in resource-constrained environments remain significant barriers to widespread adoption. Addressing these limitations is crucial for maximizing the potential of AI in revolutionizing agriculture and ensuring global food security. Artificial intelligence (AI) has emerged as a pivotal tool in modernizing agriculture, particularly in the domain of plant disease detection. This article presents a comprehensive examination of AI-driven methodologies for plant disease detection, exploring their applications and inherent limitations. Through the utilization of machine learning and computer vision techniques, AI facilitates early disease identification, precision agriculture, disease surveillance, and decision support systems. Despite these transformative capabilities, challenges such as inadequate data availability, model interpretability, and implementation in resource-constrained settings impede widespread adoption. Addressing these obstacles is imperative for fully harnessing the potential of AI in agricultural innovation, thereby safeguarding global food security and sustainability.

Nanotechnology-based Sensors for Real-time Monitoring and Assessment of Soil Health and Quality: A Review

Soil health and quality are critical factors in maintaining sustainable agriculture, ecosystem stability, and global food security. Conventional methods for assessing soil properties are often time-consuming, labor-intensive, and lack real-time monitoring capabilities. Nanotechnology has emerged as a promising approach to develop advanced sensors for rapid, in-situ, and continuous monitoring of soil health parameters. This comprehensive review discusses the recent advancements in nanotechnology-based sensors for soil health assessment, their working principles, applications, challenges, and future prospects. We highlight the potential of various nanomaterials, such as carbon nanotubes, graphene, metal oxide nanoparticles, and quantum dots, in fabricating highly sensitive, selective, and robust soil sensors. The integration of these nanosensors with wireless communication technologies and data analytics enables real-time monitoring and precision agriculture practices. Furthermore, we discuss the environmental and ecological implications of deploying nanosensors in soil and the need for standardized protocols and regulations. This review provides valuable insights into the current state-of-the-art and future directions of nanotechnology-based sensors for soil health monitoring, promoting sustainable agriculture and environmental management.

A review of the potential involvement of small RNAs in transgenerational abiotic stress memory in plants.

Crop production is increasingly threatened by the escalating weather events and rising temperatures associated with global climate change. Plants have evolved adaptive mechanisms, including stress memory, to cope with abiotic stresses such as heat, drought, and salinity. Stress memory involves priming, where plants remember prior stress exposures, providing enhanced responses to subsequent stress events. Stress memory can manifest as somatic, intergenerational, or transgenerational memory, persisting for different durations. The chromatin, a central regulator of gene expression, undergoes modifications like DNA acetylation, methylation, and histone variations in response to abiotic stress. Histone modifications, such as H3K4me3 and acetylation, play crucial roles in regulating gene expression. Abiotic stresses like drought and salinity are significant challenges to crop production, leading to yield reductions. Plant responses to stress involve strategies like escape, avoidance, and tolerance, each influencing growth stages differently. Soil salinity affects plant growth by disrupting water potential, causing ion toxicity, and inhibiting nutrient uptake. Understanding plant responses to these stresses requires insights into histone-mediated modifications, chromatin remodeling, and the role of small RNAs in stress memory. Histone-mediated modifications, including acetylation and methylation, contribute to epigenetic stress memory, influencing plant adaptation to environmental stressors. Chromatin remodeling play a crucial role in abiotic stress responses, affecting the expression of stress-related genes. Small RNAs; miRNAs and siRNAs, participate in stress memory pathways by guiding DNA methylation and histone modifications. The interplay of these epigenetic mechanisms helps plants adapt to recurring stress events and enhance their resilience. In conclusion, unraveling the epigenetic mechanisms in plant responses to abiotic stresses provides valuable insights for developing resilient agricultural techniques. Understanding how plants utilize stress memory, histone modifications, chromatin remodeling, and small RNAs is crucial for designing strategies to mitigate the impact of climate change on crop production and global food security.

Epigenetic Regulation of CYP72A385-Mediated Metabolic Resistance to Novel Auxin Herbicide Florpyrauxifen-benzyl in Echinochloa crus-galli (L.) P. Beauv.

Weed's metabolic resistance to herbicides has undermined the sustainability of herbicides and global food security. Notably, we identified an Echinochloa crus-galli (L.) P. Beauv population (R) that evolved resistance to the never-used florpyrauxifen-benzyl, in which florpyrauxifen-benzyl was metabolized faster than the susceptible E. crus-galli population (S). RNA-seq identified potential metabolism-related genes, EcCYP72A385 and EcCYP85A1, whose expression in yeast exhibited the capacity to degrade florpyrauxifen-benzyl. Region-2 in the EcCYP72A385 promoter showed significant demethylation after florpyrauxifen-benzyl treatment in the R population. DNA methyltransferase inhibitors induce EcCYP72A385 overexpression in the S population and endow it with tolerance to florpyrauxifen-benzyl. Moreover, methyltransferase-like 7A (EcMETTL7A) was overexpressed in the S population and specifically bound to the EcCYP72A385 promoter. Transgenic EcCYP72A385 in Arabidopsis and Oryza sativa L. exhibited resistance to florpyrauxifen-benzyl, whereas EcMETTL7A transgenic plants were sensitive. Overall, EcCYP72A385 is the principal functional gene for conferring resistance to florpyrauxifen-benzyl and is regulated by EcMETTL7A in E. crus-galli.

Bacterial and viral co-infections in aquaculture under climate warming: co-evolutionary implications, diagnosis, and treatment.

Climate change and the associated environmental temperature fluctuations are contributing to increases in the frequency and severity of disease outbreaks in both wild and farmed aquatic species. This has a significant impact on biodiversity and also puts global food production systems, such as aquaculture, at risk. Most infections are the result of complex interactions between multiple pathogens, and understanding these interactions and their co-evolutionary mechanisms is crucial for developing effective diagnosis and control strategies. In this review, we discuss current knowledge on bacteria-bacteria, virus-virus, and bacterial and viral co-infections in aquaculture as well as their co-evolution in the context of global warming. We also propose a framework and different novel methods (e.g. advanced molecular tools such as digital PCR and next-generation sequencing) to (1) precisely identify overlooked co-infections, (2) gain an understanding of the co-infection dynamics and mechanisms by knowing species interactions, and (3) facilitate the development multi-pathogen preventive measures such as polyvalent vaccines. As aquaculture disease outbreaks are forecasted to increase both due to the intensification of practices to meet the protein demand of the increasing global population and as a result of global warming, understanding and treating co-infections in aquatic species has important implications for global food security and the economy.

Towards real-time airborne pathogen sensing: Electrostatic capture and on-chip LAMP based detection of airborne viral pathogens

Considerable loss of life, economic slowdown, and public health risk associated with the transmission of airborne respiratory pathogens was underscored by the recent COVID-19 pandemic. Airborne transmission of zoonotic diseases such as the highly pathogenic avian influenza (HPAI) and porcine reproductive and respiratory syndrome virus (PRRSV) has caused major disruptions to domestic and global food security. Current ambient air pathogen monitoring systems involves the collection of air samples from indoor settings suspected of viral contamination, followed by subsequent processing of capture samples to determine the presence and species of airborne viral matter. Nucleic acid amplification techniques are considered the gold standard for pathogen diagnostics. Currently, the necessary extraction and purification of viral RNA from air collector systems prior to sample analysis is both time consuming and performed manually. A monitoring system with separate air sampling and biochemical detection procedures is prone to delay the response to emergent viral threats. In this paper, we present a pathogen monitoring system that overcomes these limitations related to extraction and purification of viral samples and lays the groundwork for a real-time monitor for airborne viral pathogens. We demonstrate a high flow electrostatic precipitator system, that uses small collection wells as counter electrodes for pathogen collection. Integrated reverse-transcriptase loop-mediated isothermal amplification (RT-LAMP) is used for detection of captured viral matter within wells. On-chip heating of collection wells is enabled by integrated planar heaters and small volumes of reagent (30 μL) directly to the collection wells. We present the design of such a system and show experimental results that demonstrate the use of this device for detection of aerosolized SARS-CoV-2 virus like particles (VLPs), a model pathogen for SARV-CoV-2.

Design, Synthesis, and Bioactivities of N-Heterocyclic Ureas as Strigolactone Response Antagonists against Parasitic-Weed Seed Germination.

The pernicious parasitism exhibited by root parasitic weeds such as Orobanche and Striga poses substantial peril to agricultural productivity and global food security. This deleterious phenomenon hinges upon the targeted induction of the signaling molecule strigolactones (SLs). Consequently, the identification of prospective SL antagonists holds significant promise in the realm of mitigating the infection of these pernicious weeds. In this study, we synthesized and characterized D12 based on a potent SL antagonist KK094. In vivo assay results demonstrated that D12 remarkably impedes the germination of Phelipanche aegyptiaca and Striga asiatica seeds, while also alleviating the inhibitory consequence of the SL analogue GR24 on hypocotyl elongation in Arabidopsis thaliana. The docking study and ITC assay indicated that D12 can interact strongly with the SL receptor protein, which may interfere with the binding of SL to the receptor protein as a result. In addition, the results of crop safety assessment tests showed that D12 had no adverse effects on rice seed germination and seedling growth and development. The outcomes obtained from the present study suggested that D12 exhibited promise as a prospective antagonist of SL receptors, thereby displaying substantial efficacy in impeding the seed germination process of root parasitic weeds, providing a promising basis for rational design and development of further Striga-specific herbicides.

Exploring Advanced Machine Learning Techniques for Swift Legume Disease Detection

Background: In the realm of agriculture, the insidious menace of legume crop diseases looms large, posing a significant threat to food security. This study embarks on a transformative journey, harnessing the prowess of Convolutional Neural Networks (CNNs), to fortify early disease detection in legume crops. By utilizing the inherent capabilities of deep learning, try to develop a sentinel that can identify even the most minor signs of crop diseases. Thorough data curation and preprocessing provide the system the ability to examine photos of legume leaves with previously unheard-of clarity. Methods: Meticulously crafted, the CNN architecture plays the role of a virtuoso, skilfully traversing the convolutional layers. It gains proficiency in the complex language of illness-induced aberrations via intense training, enabling it to discern between health and illness. Result: Provide remarkable results from the experimental experience using a wide range of assessment metrics. By undertaking this project, the commitment to preserving agricultural yields and, consequently, global food security is reaffirmed. It portends a more optimistic future for legume farming by indicating a ground-breaking effort at the nexus of artificial intelligence and agriculture.

Genomics-assisted speed breeding for crop improvement: present and future

Global agricultural productivity and food security are threatened by climate change, the growing world population, and the difficulties posed by the pandemic era. To overcome these challenges and meet food requirements, breeders have applied and implemented different advanced techniques that accelerate plant development and increase crop selection effectiveness. However, only two or three generations could be advanced annually using these approaches. Speed breeding (SB) is an innovative and promising technology to develop new varieties in a shorter time, utilizing the manipulation of controlled environmental conditions. This strategy can reduce the generation length from 2.5 to 5 times compared to traditional methods and accelerate generation advancement and crop improvement, accommodating multiple generations of crops per year. Beside long breeding cycles, SB can address other challenges related to traditional breeding, such as response to environmental conditions, disease and pest management, genetic uniformity, and improving resource efficiency. Combining genomic approaches such as marker-assisted selection, genomic selection, and genome editing with SB offers the capacity to further enhance breeding efficiency by reducing breeding cycle time, enabling early phenotypic assessment, efficient resource utilization, and increasing selection accuracy and genetic gain per year. Genomics-assisted SB holds the potential to revolutionize plant breeding by significantly accelerating the identification and selection of desirable genetic traits, expediting the development of improved crop varieties crucial for addressing global agricultural challenges.

Dutch landscapes have lost insect‐pollinated plants over the past 87 years

Abstract The interruption of plant‐pollinator interactions may threaten global plant diversity, food security and ecosystem stability. Recent reports of strong declines in both insects and plants point to insect decline as a driver of plant decline. However, it is still unknown whether these trends are related as plants often produce seeds without the need for insect pollinators, and to what extent insect‐pollinated plants have declined in relation to plants not pollinated by insects. In this study, we hypothesise that natural plant communities have shifted away from insect‐pollination. We combined 365,768 vegetation plots from 1930 to 2017 in the Netherlands and plant traits to assess the changes in occurrences of plants pollinated by different modes. Furthermore, we included key drivers in plant decline—specifically nitrogen, moisture and habitat types—as interaction factors to explore the persistence of the observed changes under different environmental conditions. The proportion of insect‐pollinated plants has declined while that of wind‐pollinated plants has increased over the last 87 years. This proportional change reflects an absolute decrease in the number of insect‐pollinated species and an increase in the number of wind‐pollinated species. Synthesis and applications. This study implies that Dutch landscapes are losing insect‐pollinated plant species, which is likely due, at least in part, to the decline in pollination services. Our results of quantifying the decline in insect‐pollinated plants support the necessity and urgency of taking conservation initiatives. Several management strategies and policy recommendations could be applied to alleviate the decline of insect‐pollinated plants and ensure crop safety. For example, conserving natural environments by reducing nitrogen deposition may support local plants and insect pollinators. Additionally, there is a particular need for focused efforts to protect natural grasslands, as these areas harbour many insect‐pollinated plants, which have experienced declines. Finally, monitoring and assessing the state of both pollinators and (insect‐pollinated) plants is needed to assess the progress of conservation measures. While recognising the interdependence of pollinators and pollinated plants, it is crucial to extend efforts beyond pollinator conservation alone to effectively safeguard insect‐pollinated plants and ensure crop safety.

Conflict in Ukraine and the unsettling ripples: implications on food systems and development in North Africa

AbstractThe ongoing conflict in Ukraine has profoundly impacted food systems in North Africa. This paper aims to analyze the impact of the conflict on food security in North Africa and the potential long-term consequences for the global food system. The research explores both scholarly and grey literature, including government reports, academic articles, and news articles. The findings indicate that food systems in North Africa have been particularly affected by the conflict in Ukraine, owing to its influence on the global economy, trade dynamics, and food prices. The consequent high fertilizer prices have also affected local food production, decreasing yields and increasing food prices. However, those countries with substantial financial resources (cf. Algeria) will likely be able to mitigate the adverse effects on their citizens. In contrast, countries with limited resources (cf. Egypt, Morocco, and Tunisia) or failed states (cf. Libya) may struggle to ensure the food security of their populations. The findings highlight the importance of considering these impacts when addressing global food security challenges. The food security situation in North Africa serves as a reminder of the interconnectivity of global food systems and the need for continued efforts to ensure food security for all.

Deep Learning-Based Leaf Disease Detection in Crop Using Images for Agricultural Application

The "Leaf Disease Detection" system addresses the critical challenge of plant diseases in agriculture through the implementation of an automated solution leveraging deep learning techniques. In this comprehensive endeavor, convolutional neural networks (CNNs), specifically DenseNet-121, ResNet-50, VGG-16, and Inception V4, are fine-tuned for efficient and accurate identification of plant diseases. The project utilizes the Plant Village dataset, encompassing 54,305 images across 38 plant disease classes, to conduct a comparative analysis of model performance. DenseNet-121 emerged as the top-performing model, achieving an exceptional 99.81% classification accuracy, surpassing other state-of-the-art models. The system's methodology strategically employs transfer learning to overcome computational challenges associated with training deep CNN layers. This approach, coupled with the multi-class classification strategy, proves robust in handling diverse plant species and diseases within each class. The results highlight the superior efficiency of transfer learning in comparison to building models from scratch, showcasing the potential for real-world applications in agriculture. The system's success is attributed to the careful optimization of hyper parameters and the adoption of advanced deep learning techniques, offering a promising avenue for automated and accurate plant disease detection, with implications for improving agricultural practices, minimizing economic losses, and ensuring global food security.

Biological Approaches for Sustainable Pest and Disease Management in Pulse Crops

Pulse crops, including lentils, peas, chickpeas, and beans, play a crucial role in addressing global food security and nutritional needs. However, their production is often hampered by various pests and diseases, leading to significant yield losses. Conventional pest and disease management practices, heavily reliant on synthetic chemical pesticides, have raised concerns about environmental sustainability, human health, and the development of resistance in target organisms. In recent years, biological approaches have emerged as promising alternatives for sustainable pest and disease management in pulse crops. This review provides a comprehensive overview of various biological control strategies, including the use of beneficial microorganisms, plant extracts, and other eco-friendly methods. The review discusses the mode of action, efficacy, and potential applications of these approaches in combating major pests and diseases affecting pulse crops. Additionally, it highlights the challenges and future prospects of integrating biological control methods into integrated pest and disease management programs. By adopting these sustainable practices, pulse crop production can be enhanced while minimizing the environmental footprint and promoting long-term ecological balance. The review serves as a valuable resource for researchers, extension specialists, and stakeholders in the agricultural sector, emphasizing the importance of biological approaches in achieving sustainable and resilient pulse crop production systems.

A new approach to combating illegal, unreported, and unregulated fishing: analysis of the WTO Agreement on Fisheries Subsidies

Harmful subsidies awarded by states facilitate illegal, unreported, and unregulated (IUU) fishing, which causes negative impacts on ocean ecosystems, seafood value chains, society, and global food security. The World Trade Organization Agreement on Fisheries Subsidies, adopted on June 17, 2022, aims to improve global fishery governance through trade measures and is regarded as a major step toward the achievement of the United Nations 2030 Sustainable Development Goals. The objective of this study is to offer a better insight into the interpretation and future implementation of the WTO Agreement on Fisheries Subsidies. Based on the status quo of international and regional fishery governance legal systems and management regimes in the regulation of IUU fishing, this study reviews the legislative process of the WTO Agreement on Fisheries Subsidies, analyzes five main controversial issues, and explores the conflicts of interests of different countries during the discussion. In the future, states should promote the transformation of the fisheries sector by reducing harmful subsidies for IUU fishing and enhancing cooperation among coastal states, flag states, port states and relevant RFMOs.

Microbacterium azadirachtae CNUC13 Enhances Salt Tolerance in Maize by Modulating Osmotic and Oxidative Stress

Soil salinization is one of the leading threats to global ecosystems, food security, and crop production. Plant growth-promoting rhizobacteria (PGPRs) are potential bioinoculants that offer an alternative eco-friendly agricultural approach to enhance crop productivity from salt-deteriorating lands. The current work presents bacterial strain CNUC13 from maize rhizosphere soil that exerted several PGPR traits and abiotic stress tolerance. The strain tolerated up to 1000 mM NaCl and 30% polyethylene glycol (PEG) 6000 and showed plant growth-promoting (PGP) traits, including the production of indole-3-acetic acid (IAA) and siderophore as well as phosphate solubilization. Phylogenetic analysis revealed that strain CNUC13 was Microbacterium azadirachtae. Maize plants exposed to high salinity exhibited osmotic and oxidative stresses, inhibition of seed germination, plant growth, and reduction in photosynthetic pigments. However, maize seedlings inoculated with strain CNUC13 resulted in significantly improved germination rates and seedling growth under the salt-stressed condition. Specifically, compared with the untreated control group, CNUC13-treated seedlings exhibited increased biomass, including fresh weight and root system proliferation. CNUC13 treatment also enhanced photosynthetic pigments (chlorophyll and carotenoids), reduced the accumulation of osmotic (proline) and oxidative (hydrogen peroxide and malondialdehyde) stress indicators, and positively influenced the activities of antioxidant enzymes (catalase, superoxide dismutase, and peroxidase). As a result, CNUC13 treatment alleviated oxidative stress and promoted salt tolerance in maize. Overall, this study demonstrates that M. azadirachtae CNUC13 significantly enhances the growth of salt-stressed maize seedlings by improving photosynthetic efficiency, osmotic regulators, oxidative stress resilience, and antioxidant enzyme activity. These findings emphasize the potential of utilizing M. azadirachtae CNUC13 as a bioinoculant to enhance salt stress tolerance in maize, providing an environmentally friendly approach to mitigate the negative effects of salinity and promote sustainable agriculture.

Antifungal plant flavonoids identified in silico with potential to control rice blast disease caused by Magnaporthe oryzae.

Rice blast disease, caused by the fungus Magnaporthe oryzae, poses a severe threat to rice production, particularly in Asia where rice is a staple food. Concerns over fungicide resistance and environmental impact have sparked interest in exploring natural fungicides as potential alternatives. This study aimed to identify highly potent natural fungicides against M. oryzae to combat rice blast disease, using advanced molecular dynamics techniques. Four key proteins (CATALASE PEROXIDASES 2, HYBRID PKS-NRPS SYNTHETASE TAS1, MANGANESE LIPOXYGENASE, and PRE-MRNA-SPLICING FACTOR CEF1) involved in M. oryzae's infection process were identified. A list of 30 plant metabolites with documented antifungal properties was compiled for evaluation as potential fungicides. Molecular docking studies revealed that 2-Coumaroylquinic acid, Myricetin, Rosmarinic Acid, and Quercetin exhibited superior binding affinities compared to reference fungicides (Azoxystrobin and Tricyclazole). High throughput molecular dynamics simulations were performed, analyzing parameters like RMSD, RMSF, Rg, SASA, hydrogen bonds, contact analysis, Gibbs free energy, and cluster analysis. The results revealed stable interactions between the selected metabolites and the target proteins, involving important hydrogen bonds and contacts. The SwissADME server analysis indicated that the metabolites possess fungicide properties, making them effective and safe fungicides with low toxicity to the environment and living beings. Additionally, bioactivity assays confirmed their biological activity as nuclear receptor ligands and enzyme inhibitors. Overall, this study offers valuable insights into potential natural fungicides for combating rice blast disease, with 2-Coumaroylquinic acid, Myricetin, Rosmarinic Acid, and Quercetin standing out as promising and environmentally friendly alternatives to conventional fungicides. These findings have significant implications for developing crop protection strategies and enhancing global food security, particularly in rice-dependent regions.

EFFECT OF OKORO [(Albizia zygia (J.F.) Macbr)] LEAFY BIOMASS AND NPK FERTILISER ON THE GROWTH AND YIELD OF SWEET PEPPER (Capsicum annum L.)

Agricultural productivity and sustainable crop management are pivotal aspects of global food security and economic stability. The quest for efficient and environmentally friendly practices in crop production has led to a surge in research exploring the utilisation of organic materials alongside conventional fertilisers to enhance crop growth and yield. An experiment was conducted over a growing period of three months, starting in August 2023 at the research field of Kwame Nkrumah University of Science and Technology, Kumasi-Ghana, to investigate the effects of Albizia zygia leafy biomass in combination with NPK fertiliser on the growth and yield of sweet pepper (Capsicum annum L.). A randomised complete block design was employed with four treatment groups replicated four times, including various combinations of A. zygia leafy biomass and NPK fertiliser, alongside control groups of sole fertiliser application and untreated plots (T1). The treatments were as follows: T1 = No biomass, no NPK (control); T2 = 0.5348 kg of A. zygia leafy biomass per 4.86 m2 (1100.5 kg/ha of A. zygia leafy biomass); T3 = 0.2463 kg of NPK per 4.86 m2 (506.7 kg/ha of NPK); and T4 = 0.2674 kg of A. zygia leafy biomass per 4.86 m2 + 0.1231 kg of NPK (550.3 kg/ha of A. zygia leafy biomass + 253.4 kg/ha of NPK). The assessed parameters were plant height, number of leaves, number of branches, fruit yield and fresh fruit weight. Significant variations (p ˂ 0.05) were observed in the growth parameters (plant height, number of leaves, number of branches) and yield attributes (fruit yield and fresh fruit weight) of sweet pepper among the treatments. The combined application of A. zygia leafy biomass and NPK fertiliser (T4) exhibited increased effects on plant height, number of leaves, number of branches, fruit yield and fresh fruit weight compared to individual treatments and control groups (p ˂ 0.05). Notably, the treatment combining A. zygia leafy biomass and NPK fertiliser (T4) demonstrated a substantial increase in plant height (44.58 cm), a significant improvement in the number of leaves (42.98) and a remarkable enhancement in the number of branches (11.33) compared to the sole applications and the control group. Furthermore, the combined treatment significantly increased (p ˂ 0.05) the yield parameters, including fruit yield and fresh fruit weight per hectare, showcasing an increase of 8796/ha and 23.91 t/ha, respectively, compared to sole fertiliser application and the control. The findings from this study demonstrated that the incorporation of A. zygia leafy biomass, either solely or in combination with NPK fertiliser, positively impacted the growth and yield of sweet pepper plants. These results highlight the potential of A. zygia leafy biomass as a valuable organic amendment for sustainable and enhanced crop production, offering promising implications for agricultural practices aimed at improving yield and plant growth.

Prospects of probiotics in beekeeping: a review for sustainable approach to boost honeybee health.

Honeybees are vital for global crop pollination, making indispensable contributions to agricultural productivity. However, these vital insects are currently facing escalating colony losses on a global scale, primarily attributed to parasitic and pathogenic attacks. The prevalent response to combat these infections may involve the use of antibiotics. Nevertheless, the application of antibiotics raises concerns regarding potential adverse effects such as antibiotic resistance and imbalances in the gut microbiota of bees. In response to these challenges, this study reviews the utilization of a probiotic-supplemented pollen substitute diet to promote honeybee gut health, enhance immunity, and overall well-being. We systematically explore various probiotic strains and their impacts on critical parameters, including survival rate, colony strength, honey and royal jelly production, and the immune response of bees. By doing so, we emphasize the significance of maintaining a balanced gut microbial community in honeybees. The review also scrutinizes the factors influencing the gut microbial communities of bees, elucidates the consequences of dysbiosis, and evaluates the potential of probiotics to mitigate these challenges. Additionally, it delineates different delivery mechanisms for probiotic supplementation and elucidates their positive effects on diverse health parameters of honeybees. Given the alarming decline in honeybee populations and the consequential threat to global food security, this study provides valuable insights into sustainable practices aimed at supporting honeybee populations and enhancing agricultural productivity.