Sustainable Food Security Research Articles

Plant Disease: A Growing Threat to Global Food Security

The escalating global population has led to an increased demand for both quantity and quality in food production. Throughout history, plant diseases have posed significant threats to agricultural output by causing substantial food losses annually while also compromising product quality. Accurate identification of pathogens, clarifying the pathogenic mechanism of pathogens, and understanding the interaction between pathogens and hosts are important for the control of plant diseases. This Special Issue, “Research Progress on Pathogenicity of Fungi in Crops”, belongs to the section “Pest and Disease Management” of Agronomy. It contains research papers on the identification and phylogeny of fungal pathogens, the molecular genetics of plant fungal pathogens, the molecular mechanisms of fungal pathogenicity, and the molecular basis of the interaction between fungi and crops. These studies encapsulate efforts to understand disease systems within current genomics, transcriptomics, proteomics, and metabolomics studies, highlighting research findings that could be future targets for crop disease and pest control. The studies presented in this Special Issue promote the progress of fungal pathogenicity research in crops and provide a scientific basis for future disease control, which is of great significance for sustainable agricultural development and global food security.

Digital Mapping and Scenario Prediction of Soil Salinity in Coastal Lands Based on Multi-Source Data Combined with Machine Learning Algorithms

Salinization is a major soil degradation process threatening ecosystems and posing a great challenge to sustainable agriculture and food security worldwide. This study aimed to evaluate the potential of state-of-the-art machine learning algorithms in soil salinity (EC1:5) mapping. Further, we predicted the distribution patterns of soil salinity under different future scenarios in the Yellow River Delta. A geodatabase comprising 201 soil samples and 19 conditioning factors (containing data based on remote sensing images such as Landsat, SPOT/VEGETATION PROBA-V, SRTMDEMUTM, Sentinel-1, and Sentinel-2) was used to compare the predictive performance of empirical bayesian kriging regression, random forest, and CatBoost models. The CatBoost model exhibited the highest performance with both training and testing datasets, with an average MAE of 1.86, an average RMSE of 3.11, and an average R2 of 0.59 in the testing datasets. Among explanatory factors, soil Na was the most important for predicting EC1:5, followed by the normalized difference vegetation index and soil organic carbon. Soil EC1:5 predictions suggested that the Yellow River Delta region faces severe salinization, particularly in coastal zones. Among three scenarios with increases in soil organic carbon content (1, 2, and 3 g/kg), the 2 g/kg scenario resulted in the best improvement effect on saline–alkali soils with EC1:5 > 2 ds/m. Our results provide valuable insights for policymakers to improve saline–alkali land quality and plan regional agricultural development.

A Multitask Learning-Based Vision Transformer for Plant Disease Localization and Classification

Plant disease detection is a critical task in agriculture, essential for ensuring crop health and productivity. Traditional methods in this context are often labor-intensive and prone to errors, highlighting the need for automated solutions. While computer vision-based solutions have been successfully deployed in recent years for plant disease identification and localization tasks, these often operate independently, leading to suboptimal performance. It is essential to develop an integrated solution combining these two tasks for improved efficiency and accuracy. This research proposes the innovative Plant Disease Localization and Classification model based on Vision Transformer (PDLC-ViT), which integrates co-scale, co-attention, and cross-attention mechanisms and a ViT, within a Multi-Task Learning (MTL) framework. The model was trained and evaluated on the Plant Village dataset. Key hyperparameters, including learning rate, batch size, dropout ratio, and regularization factor, were optimized through a thorough grid search. Early stopping based on validation loss was employed to prevent overfitting. The PDLC-ViT model demonstrated significant improvements in plant disease localization and classification tasks. The integration of co-scale, co-attention, and cross-attention mechanisms allowed the model to capture multi-scale dependencies and enhance feature learning, leading to superior performance compared to existing models. The PDLC-ViT model evaluated on two public datasets achieved an accuracy of 99.97%, a Mean Average Precision (MAP) of 99.18%, and a Mean Average Recall (MAR) of 99.11%. These results underscore the model's exceptional precision and recall, highlighting its robustness and reliability in detecting and classifying plant diseases. The PDLC-ViT model sets a new benchmark in plant disease detection, offering a reliable and advanced tool for agricultural applications. Its ability to integrate localization and classification tasks within an MTL framework promotes timely and accurate disease management, contributing to sustainable agriculture and food security.

The involvement of phytohormones in plant–pathogen interaction

Plant–pathogen interactions involve intricate signaling networks that coordinate the plant immune response. Recognition of pathogens through pattern recognition receptors (PRRs) triggers activation of mitogen-activated protein kinase (MAPK) pathways, initiating a cascade of defense mechanisms. Central to these responses is the synthesis of phytohormones such as salicylic acid (SA), auxins–indole-3-acetic acid (IAA), and gibberellins–gibberellic acid (GA), pivotal for immune activation. This review explores the multifaceted roles of these phytohormones in plant immunity, drawing on recent findings from Arabidopsis thaliana and Gossypium hirsutum studies. The review discusses MAPK-mediated activation of TGA1/4 (TGACG sequence-specific binding protein 1/4) transcription factors enhancing SA biosynthesis via isochorismate synthase (ICS). Increased SA levels activate NPR1, promoting gene expression in immune-related pathways including systemic acquired resistance (SAR). Concurrently, pathogen-induced IAA synthesis activates auxin-responsive genes crucial for immune responses. Elevated biosynthesis of IAA from L-tryptophan activates these genes by degrading repressor molecules. IAA acts antagonistically to SA, conserving energy during pathogen infection. Additionally, GA is vital for plant growth and development, operating DELLA (Asp–Glu–Leu–Leu–Ala) protein degradation with the formation of a complex with gibberellin insensitive dwarf 1 (GID1). Once DELLA prevents releasing GA-related response reactions, it is extremelly crucial for GA actions. In general, the review explores the intricate interplay between SA, IAA, and GA, highlighting SA's antagonistic regulation of GA signaling and the synergistic effects of auxin and GA. Understanding these hormone–mediated pathways is crucial for elucidating precise mechanisms underlying plant immunity. Insights gained could inform strategies to enhance plant resistance against pathogens, contributing to sustainable agriculture and global food security efforts.

Climate Change Impacts on Legume Physiology and Ecosystem Dynamics: A Multifaceted Perspective

As valuable sources of plant-based protein, leguminous vegetables (grain legumes) are essential for global food security and contribute to body growth and development in humans as well as animals. Climate change is a major challenge for agriculture development that creates major problems for the growth and development of plants. However, legume productivity is threatened by climate change factors, including rising temperatures, shifting precipitation patterns, increased atmospheric carbon dioxide levels, intensified extreme events, and altered pest/pathogen activity. This review synthesizes approximately 136 studies to assess the climate effects on major legume crops. Under all the global emissions trajectories, the mean temperatures are projected to rise beyond the optimal legume growing thresholds by 2050, carrying yield reductions between 10 and 49% for beans, soybeans, cowpeas, and lentils without adaptation measures. The elevated carbon dioxide may transiently enhance the yields up to 18%, but the benefits dramatically decline above 550 ppm and cannot offset the other climate impacts. Altered rainfall along with recurrent drought and heat waves are also expected to decrease the legume crop yields, seed quality, and soil nitrogen levels worldwide. Furthermore, the proliferation of legume pests and fungal diseases poses significant risks, amplified by climate shifts in 84% of the reviewed studies. These multifaceted impacts threaten the productivity gains in leguminous vegetables essential to sustainably meeting the global protein demand. Realizing resilience will require the accelerated development of heat/drought-tolerant legume varieties, enhanced climate-informed agronomic practices, strong policy interventions, and social safety nets explicitly supporting legume producers, in addition to the policies/steps that governments are taking to address the challenges of the climate crisis. This review highlights the essential adaptations and mechanisms required for legume crops to thrive and fulfill their significant roles in global nutrition. It explores how these crops can be improved to better withstand the environmental stresses, enhance their nutritional profiles, and increase their yields. Additionally, the review discusses the importance of legumes in sustainable agriculture and food security, emphasizing their potential to address the future challenges in feeding the growing global population. By focusing on these critical aspects, the review aims to underscore the importance of legumes in ensuring a healthy and sustainable food supply.

Sustainable rural economy and food security: An integrated approach to the circular agricultural model

The lack of resources and increasing damage are major obstacles to sustainable economic progress. Conventional farming methods, known for their energy consumption and resulting pollution, need changes. This study focuses on agriculture, an approach inspired by natural ecological cycles that aim to promote sustainable development in rural areas through efficient resource reuse. The connection between agriculture and rural economies, along with strategies for their combined advancement, is an area that requires more exploration and thorough empirical analysis. The research involves an energy analysis methodology tailored for use in regions to assess the benefits and environmental impacts of implementing circular agriculture for sustainable rural economic growth. A multi-objective decision-making approach using TOPSIS is employed to enhance agricultural policy formulation and decision-making processes. The study concludes by developing a model that considers production, processing, recycling, and socioeconomic aspects to delve into the development of circular agriculture within rural communities and propose relevant strategies. The uniqueness of this research lies in its combination of agriculture and the coordinated advancement of rural economies, which offers a fresh viewpoint and approach to sustainable farming methods and robust rural economic development. The results contribute to the circular agriculture literature body and provide practical guidance for policymakers and farmers.

Molecular Cloning and Functional Identification of a Pericarp- and Testa-Abundant Gene's (AhN8DT-2) Promoter from Arachis hypogaea.

Cultivated peanut (Arachis hypogaea L.) is a key oil- and protein-providing legume crop of the world. It is full of nutrients, and its nutrient profile is comparable to that of other nuts. Peanut is a unique plant as it showcases a pegging phenomenon, producing flowers above ground, and after fertilization, the developing peg enters the soil and produces seeds underground. This geocarpic nature of peanut exposes its seeds to soil pathogens. Peanut seeds are protected by an inedible pericarp and testa. The pericarp- and testa-specific promoters can be effectively used to improve the seed defense. We identified a pericarp- and testa-abundant expression gene (AhN8DT-2) from available transcriptome expression data, whose tissue-specific expression was further confirmed by the qRT-PCR. The 1827bp promoter sequence was used to construct the expression vector using the pMDC164 vector for further analysis. Quantitative expression of the GUS gene in transgenic Arabidopsis plants showed its high expression in the pericarp. GUS staining showed a deep blue color in the pericarp and testa. Cryostat sectioning of stained Arabidopsis seeds showed that expression is only limited to seed coat (testa), and staining was not present in cotyledons and embryos. GUS staining was not detected in any other tissues, including seedlings, leaves, stems, and roots, except for some staining in flowers. Under different phytohormones, this promoter did not show an increase in expression level. These results indicated that the AhN8DT-2 promoter drives GUS gene expression in a pericarp- and testa-specific manner. The identified promoter can be utilized to drive disease resistance genes, specifically in the pericarp and testa, enhancing peanut seed defense against soil-borne pathogens. This approach has broader implications for improving the resilience of peanut crops and other legumes, contributing to sustainable agricultural practices and food security.

From 'Farm to Fork': Exploring the Potential of Nutrient-Rich and Stress-Resilient Emergent Crops for Sustainable and Healthy Food in the Mediterranean Region in the Face of Climate Change Challenges.

In the dynamic landscape of agriculture and food science, incorporating emergent crops appears as a pioneering solution for diversifying agriculture, unlocking possibilities for sustainable cultivation and nutritional bolstering food security, and creating economic prospects amid evolving environmental and market conditions with positive impacts on human health. This review explores the potential of utilizing emergent crops in Mediterranean environments under current climate scenarios, emphasizing the manifold benefits of agricultural and food system diversification and assessing the impact of environmental factors on their quality and consumer health. Through a deep exploration of the resilience, nutritional value, and health impacts of neglected and underutilized species (NUS) such as quinoa, amaranth, chia, moringa, buckwheat, millet, teff, hemp, or desert truffles, their capacity to thrive in the changing Mediterranean climate is highlighted, offering novel opportunities for agriculture and functional food development. By analysing how promoting agricultural diversification can enhance food system adaptability to evolving environmental conditions, fostering sustainability and resilience, we discuss recent findings that underscore the main benefits and limitations of these crops from agricultural, food science, and health perspectives, all crucial for responsible and sustainable adoption. Thus, by using a sustainable and holistic approach, this revision analyses how the integration of NUS crops into Mediterranean agrifood systems can enhance agriculture resilience and food quality addressing environmental, nutritional, biomedical, economic, and cultural dimensions, thereby mitigating the risks associated with monoculture practices and bolstering local economies and livelihoods under new climate scenarios.

Community garden management for resilient cities: A case study in suburban Tokyo during the COVID-19 pandemic

Numerous studies underscore the role of community gardens in sustaining food security, physical and mental health, and social networks during the COVID-19 pandemic, contributing to community resilience in different contexts of each country. Despite the rich history of urban gardening, Japan remains a geographical gap. This study conducted a mixed-method case study in suburban Tokyo and addresses the unique response of community gardeners to the pandemic within the Japanese context. The survey revealed that gardeners proactively established rules to navigate the crisis quickly through discussion and sustained their gardening activities. The findings also showed that their continuing activities helped the gardeners maintaining physical and mental health, and notably keeping their ikigai, sense of purpose in life in the unusual days. Thus, this study provided new evidence that community gardens may contribute to urban resilience, which indicates the significance of incorporating them into urban green space planning as a preparatory measure for future social crises.

Comparative Analysis Highlights Uniconazole's Efficacy in Enhancing the Cold Stress Tolerance of Mung Beans by Targeting Photosynthetic Pathways.

Soybean (Glycine max) and mung bean (Vigna radiata) are key legumes with global importance, but their mechanisms for coping with cold stress-a major challenge in agriculture-have not been thoroughly investigated, especially in a comparative study. This research aimed to fill this gap by examining how these two major legumes respond differently to cold stress and exploring the role of uniconazole, a potential stress mitigator. Our comprehensive approach involved transcriptomic and metabolomic analyses, revealing distinct responses between soybean and mung bean under cold stress conditions. Notably, uniconazole was found to significantly enhance cold tolerance in mung bean by upregulating genes associated with photosynthesis, while its impact on soybean was either negligible or adverse. To further understand the molecular interactions, we utilized advanced machine learning algorithms for protein structure prediction, focusing on photosynthetic pathways. This enabled us to identify LOC106780309 as a direct binding target for uniconazole, confirmed through isothermal titration calorimetry. This research establishes a new comparative approach to explore how soybean and mung bean adapt to cold stress, offers key insights to improve the hardiness of legumes against environmental challenges, and contributes to sustainable agricultural practices and food security.

Applications of Artificial Intelligence in Wheat Breeding for Sustainable Food Security

In agriculture, especially in crop breeding, innovative approaches are required to address the urgent issues posed by climate change and global food security. Artificial intelligence (AI) is a revolutionary technology in wheat breeding that provides new approaches to improve the ability of crops to withstand and produce higher yields in response to changing climate circumstances. This review paper examines the incorporation of artificial intelligence (AI) into conventional wheat breeding methods, with a focus on the contribution of AI in tackling the intricacies of contemporary agriculture. This review aims to assess the influence of AI technologies on enhancing the efficiency, precision, and sustainability of wheat breeding projects. We conduct a thorough analysis of recent research to evaluate several applications of artificial intelligence, such as machine learning (ML), deep learning (DL), and genomic selection (GS). These technologies expedite the swift analysis and interpretation of extensive datasets, augmenting the process of selecting and breeding wheat varieties that are well-suited to a wide range of environmental circumstances. The findings from the examined research demonstrate notable progress in wheat breeding as a result of artificial intelligence. ML algorithms have enhanced the precision of predicting phenotypic traits, whereas genomic selection has reduced the duration of breeding cycles. Utilizing artificial intelligence, high-throughput phenotyping allows for meticulous examination of plant characteristics under different stress environments, facilitating the identification of robust varieties. Furthermore, AI-driven models have exhibited superior predicted accuracies for crop productivity and disease resistance in comparison to conventional methods. AI technologies play a crucial role in the modernization of wheat breeding, providing significant enhancements in crop performance and adaptability. This integration not only facilitates the growth of wheat cultivars that provide large yields and can withstand stressful conditions but also strengthens global food security in the context of climate change. Ongoing study and collaboration across several fields are crucial to improving and optimizing these AI applications, ultimately enhancing their influence on sustainable agriculture.

Assessing the Human-Wildlife Conundrum in Zimbabwe: Implications for Social Work Practice

Human-wildlife conflict is a global crisis that has significantly impacted the local livelihoods of the rural populace of the world. This study aimed to examine the consequences and effects of human-wildlife conflict in Mbire District, Ward 1, Zimbabwe. This paper analysed a range of issues, including human-wildlife conflict, poaching, habitat loss, and socio-economic impacts, all of which intertwine to create a complex web of challenges with severe consequences for both humans and wildlife alike. The study was informed by the Musha/Nyumba and social conflict theories. The research used the qualitative method, where structured face-to-face interviews were conducted. Data was gathered from a sample of thirty participants and three key informants who were purposively selected to participate in the study. The study utilized a case-study research design. Data collected from the interviews were analysed to identify categories, emerging themes, and areas of agreement or disagreement in relation to the research questions. The study revealed that the consequences of human-wildlife conflicts include competition for resources, threats to human safety, crop and livestock damage, conservation concerns, and disruption of ecosystem balance. The paper concluded that human-wildlife conflict is a serious global threat to sustainable development, food security, wildlife conservation, and health, a concern that is negatively affecting people, wildlife, and the achievement of sustainable development goals. Evidence-based recommendations were provided to policymakers and stakeholders, including education initiatives, compensation and insurance schemes, land use planning, community engagement, and the development of early warning systems. This paper contributes to the ongoing debate on the economics of human-wildlife conflict and the contribution of wildlife to local livelihoods. Keywords: Human-Wildlife, Conflict, Wildlife, Zimbabwe

Climate Smart Agriculture: A Roadmap to Sustainable Food Security

Climate change (CC) and climate variability (CV) are causing irregular precipitation, rising sea levels, and frequent extreme weather events, which threaten global agricultural crop production through prolonged droughts, floods, and shifting agroclimatic zones. Addressing greenhouse gas emissions and ensuring food security are among the greatest challenges of this century. Climate Smart Agriculture (CSA) emerges as a global strategy to enhance food productivity amid these uncertainties. CSA aims to create climate-resilient agricultural systems that increase soil health, water, and nutrient efficiency, provide stable yields, and reduce greenhouse gas emissions. By improving farmers' incomes and resilience to climate impacts, CSA contributes to both climate change mitigation and adaptation. Future CSA development directions include leveraging advanced internet technology for secure agricultural information, optimizing cropping patterns and management, integrating "internet + weather" services, and implementing agricultural weather index-based insurance. These strategies offer new pathways for ecological protection, green agricultural development, and climate change mitigation.

Unveiling the salinity tolerance potential of Armenian Dandur (Portulaca oleracea L.) genotypes: Enhancing sustainable agriculture and food security

This study examines the adaptation of an undocumented halophyte, Dandur, to salt stress in different soil mediums. The Dandur plant physiological, morphological, and biochemical analyses show that it can withstand salinity stress. Dandur plants grown in clay and clay loam soil experienced significant decreases in height and stem diameter under extreme salinity conditions compared to non-saline soil. The fresh weight of root and shoot decreased by 70.4% and 84.8%, respectively, and dry weight by 48.5% and 79.7%. These findings underscore the importance of maintaining saline soil conditions for plant growth. Dandur unique ability to avoid dehydration and maintain growth traits, particularly in clay soil, holds promise for further exploration in agricultural research and food security-related issues caused by climate change in saline areas of Armenia and other European countries.

The Sweet Gains of Diversification: A Review of Intercropping Benefits in Sugarcane Farming

Sugarcane farming, a cornerstone of the global sugar and bioenergy industries, has seen a surge in interest in recent years due to the adoption of sustainable agricultural practices. One such practice, intercropping, is becoming increasingly recognized for its potential to transform the dynamics of sugarcane cultivation. As the world grapples with the challenges of sustainable agriculture and food security, the adoption of intercropping in sugarcane farming stands as a promising strategy. This review emphasizes the pivotal role of diversification in enhancing the resilience and prosperity of sugarcane farming while contributing to global agricultural sustainability. It underscores the pivotal role of intercropping in sugarcane cultivation, not only in augmenting crop yields and farmer livelihoods but also in fostering soil resilience and health.

Evaluation of the policy program for strengthening local food commodities for sustainable food security in papua

Achieving sustainable food security in Papua remains a significant challenge due to the region's heavy reliance on imported food. The policy program aimed at bolstering local food commodities is designed to promote self-sufficiency and ensure long-term food sustainability. This study evaluates the policy program focused on strengthening local food commodities in Papua, specifically targeting sago, sweet potatoes, and maize. The objective is to assess the program's effectiveness in boosting local food production and its overall contribution to sustainable food security. The research methodology integrates both qualitative and quantitative approaches, incorporating secondary data analysis from government reports, field surveys of local farmers, and in-depth interviews with key stakeholders to gain a holistic perspective. The data analysis techniques included thematic analysis for qualitative data, ensuring detailed insights, and statistical methods for quantitative data to provide robust findings. The results indicate that the policy program has increased local food commodity production by 30% over the past five years. However, significant challenges remain, including inadequate infrastructure, limited market access, and insufficient support services for farmers, which hinder the full optimization of the program's benefits. The policy initiative has positively impacted food production and sustainable food security in Papua. For long-term success, it is crucial to improve infrastructure, expand market access, and provide continuous support and training for local farmers. This will ensure the gains achieved by the policy program are maintained and further developed, leading to a more resilient local food system in Papua

The Integration Hydroponic Aquaculture Systems For Optimizing Catfish Growth Management with Arduino

Modern agriculture faces significant challenges such as limited land and declining soil fertility. The integration of hydroponic systems with aquaculture, particularly catfish farming, offers an innovative solution to enhance agricultural efficiency and productivity. This study explores the integration of hydroponic systems with aquaculture for the simultaneous cultivation of plants and catfish in a controlled environment. The research utilizes Arduino technology for monitoring temperature, pH, and water turbidity, which are essential for the health of fish and plants. The research method used is Research and Development (R&D), involving the following steps: (1) Identifying potential problems, (2) Data collection, (3) Product design, (4) Design validation, (5) Design revision, and (6) Product testing. The results indicate that integrating hydroponic systems with Arduino technology improves the efficiency of monitoring and managing the cultivation environment, positively impacting plant and catfish growth. The implementation of this system shows an increase in plant nutrient content and better fish health. And then, this research significantly contributes to the development of sustainable agriculture and global food security through the adoption of innovative technology.

THE FACTORS IMPACTING OVER ORGANIC PRODUCT’S MARKET: A STUDY OF KUMAUN REGION OF UTTARAKHAND

Since ancient times, India has employed the organic farming technique, which is primarily concerned with producing agricultural products that are sustainable in a clean, unpolluted environment. In order to achieve the necessary agricultural production for human consumption, organic production methods make use of natural resources, maintaining the ecosystem and ecology alive and well. Using naturally occurring resources as inputs, such as organic wastes, farm, animal, and crop wastes, aquatic wastes, other biological materials, and beneficial microbes, is the environmental focus of organic production. Biofertilizers and biocontrol agents are used to release nutrients into crops and shield them from insect pests and diseases in order to increase agricultural productivity. It is imperative that farms move to organic practices. India, a nation that depends heavily on agriculture, must take measures to address the issue of its rapidly expanding population.Although there has been a noticeable movement in people's knowledge of organic food, it appears to be quite gradual. The cultivation of organic crops using the organic farming technique is gaining steam on a global scale. To achieve sustained food, livelihood, and environmental security, a range of alternatives to chemical intensive agriculture must be developed. The present study is an Exploratory cum Descriptive Research in nature with a sample size of 200 customers and various statistical tools such as frequency distribution, percentage, arithmetic mean and general linear Univariate model used. The respondents from different age group, different qualifications and others agreed that there should be an immediate improvement in the product accessibility in the market and the government as well as the producers, should play a key role in it. The study concludes that Organic product’s Market availability needs to improve from Govt. as well as producers both.

Biofertilizer Production using Phosphate-solubilizing Pseudomonas spp. Isolated from Rhizosphere Soil: Towards Indigenous Biofertilizer for Enhanced Crop Productivity in Katsina, Nigeria

Study’s Novelty/Excerpt This study offers an approach to sustainable agriculture by isolating and identifying phosphate-solubilizing Pseudomonas species from the rhizosphere soil of Wagini ward, Katsina state, for the production of biofertilizers. The research highlights the significant phosphate-solubilizing activity of these native strains, which enhances phosphorus availability to plants through the secretion of organic acids and enzymes. By demonstrating the positive effects of these Pseudomonas-based biofertilizers on maize, beans, and millet, this study provides valuable insights into the development of eco-friendly, cost-effective biofertilizers tailored to local agroecosystems, thereby promoting sustainable agricultural practices in Nigeria. Full Abstract The utilization of biofertilizers holds promise as a sustainable approach to enhance soil fertility and crop productivity while reducing reliance on chemical fertilizers. Beyond nitrogen, phosphorus is integral to various aspects of plant metabolism, including cell division, growth, development, sugar breakdown, and nuclear transport. The present study focuses on isolating Pseudomonas as phosphate-solubilizing bacteria from the rhizosphere soil to produce biofertilizer. Ten samples of rhizosphere soil samples were collected from agricultural fields in Wagini ward, Batsari Local Government area, Katsina state. The isolation and identification of Pseudomonas species from the soil samples were conducted using standard microbiological techniques, followed by screening for plant growth-promoting traits (phosphate solubilization). Subsequently, selected Pseudomonas species exhibiting robust phosphate solubilization were assessed for their efficacy in biofertilizer production, after which the produced biofertilizer was tested on maize, beans, and millet. The formulated biofertilizers demonstrated remarkable positive effects on the tested crops’ growth compared to those that were not treated with the Pseudomonas-based biofertilizer after seven days of cultivation under controlled conditions. The results of this study revealed that the isolated Pseudomonas strains exhibited significant phosphate-solubilizing activity. This indicates their potential to release phosphorus from insoluble forms, making it more accessible to plants. The solubilization activity was attributed to the secretion of organic acids and enzymes by the Pseudomonas strains, which can dissolve complex phosphates. This study underscores the importance of tacking native microbial resources for the development of eco-friendly and cost-effective biofertilizers tailored to local agroecosystems, thereby contributing to sustainable agricultural intensification and food security in Nigeria.

Regional Superior Products as The Key to Sustainable Food Security in Jember Regency, Indonesia

Understanding the development planning priorities and commodity sub-sector in Jember Regency, it is necessary to acknowledge the prime sub-sector and the primary commodity sector in Jember Regency. Regional products should be able to prioritize the sub-sector and the preferred crop, prime and which is considered a sub-sector basis to optimize the food security in the region. The research was conducted from 2016 to 2021 by several analysis methods: Location Quotient, Analytical Hierarchy Process, and Exponential Comparative Method. The criteria used are based on seven normative criteria. The results showed that plantation and horticultural crops were the basis of sectors in the 2016-2020 survey, with values of 2,1036 and 1,3879. Based on the analytical hierarchy process and exponential comparative method analysis, it is seen that there are many leading commodities in the agriculture sector. These commodities are orange fruit, durian, banana, mushrooms, chili, coffee, and sugarcane.