Therapeutic potential of natural plant substances for the control of avian infectious bronchitis virus

Avian infectious bronchitis (IB) is one of the foremost avian pathologies and is caused by a coronavirus with worldwide distribution. In addition to its infectivity, the appearance of new variants and strains makes this pathology particularly difficult to control, which represents a threat to the poultry sector. Natural substances have long been used as therapeutic sources and boosters for vaccines since vaccines alone do not provide complete protection due to continuous mutations of the infectious bronchitis virus (IBV). To explore other remedies to fight IBV, several researchers have turned to using medicinal plants and extracting active ingredients with antiviral properties. The quest for alternative therapies is particularly relevant given the Sars-CoV-2 outbreak, a human coronavirus that shares similarities with IBV, such as its mutation rates and health complications. This article is a systematic review of natural products used against IBV. Thirteen natural products, including plants, essential oils, and mixtures, were identified in this study, and all showed antiviral activity against IBV, with variable effectiveness. Although the efficacy of these active substances has been established and demonstrated by scientific methods, further and more in-depth studies should be carried out to confirm the results, determine the mechanisms of action, and validate their use as a treatment or adjuvant. Keywords: Coronavirus, IBV, plants, antiviral, poultr

Legume crops enhance water use efficiency under intercropping system with wheat

A comparative analysis of three legume crops (faba bean, peas, and clover) as intercrops with wheat was conducted under three irrigation treatments (100%, 85%, and 70% ETc) to evaluate their contributions to enhancing the complementary effect that improves water usage and wheat production. The irrigation water applied to wheat intercropping systems was equivalent to that applied to sole wheat, indicating that both intercrops utilized the irrigation designated for sole wheat. The faba bean-wheat intercropping system exhibited the greatest water utilization and soil accessible nitrogen across the three irrigation regimens. The production of intercropped wheat was maximized in the peas intercropping system, in contrast to the yield of sole wheat. The intercropping system of peas achieved the highest land equivalent ratio (LER), water equivalent ratio (WER), and change in water use, indicating enhanced water use efficiency. In an irrigation scenario of 85% ETc, the LER and WER for the peas intercropping system exceeded those of the faba bean intercropping system under 100% ETc. The intercropping system with peas had the highest monetary advantage index value. This suggests that, in the context of limited water resources, intercropping peas with wheat is advisable to enhance the utilization of available water resources.  Keywords: faba bean, peas, clover, available soil N, land and water equivalent ratios, change in water use, momentary advantage inde

Impact of foliar application of moringa leaf extract on growth and yield of different cultivars of cucumber (Cucumis sativus) in Nigeria

Extreme dependency on synthetic fertilizers and other agricultural inputs like pesticides and herbicides poses risks to environmental and health hazards and has driven the quest for more justifiable and eco-friendly approaches.  A field experiment was conducted during the 2024 growing season at Federal University Dutse Teaching and Research Farm, to examine the potential of Moringa Leaf Extract (MLE) as a natural, plant-based biostimulant to improve cucumber (Cucumis sativus) productivity. Three cucumber varieties were used Monalisa F1, Saira F1, and Poinsett, and were laid in a Randomized Complete Block Design with three replications. Data on crop growth and yield components were collected and analyzed. Except for the Number of branches and Number of fruits per plant, MLE application significantly enhanced most traits of cucumber, including days to 50% flowering, number of Fruit diameter, vine length, and number of leaves, Poinsett variety had high fruit length compared to Monelisa F1 and Saira F1, while Monalisa F1 had a high percentage of flowering compared to Poinsett and Saira F1. The application of MLE proved to be an effective biostimulant offering an alternative and environmentally friendly approach to enhance the productivity of cucumber in Sudan Savannah Zone of Nigeria. Keyword: Bio-stimulant, Cucumber, Moringa leaf extract, Yield, Varietie

Massive almond tree mortality in the central High Atlas, Morocco

Morocco has been experiencing six consecutive years of drought due to a decline in rainfall linked to climate change and this have threatened water supplies and hit agriculture and the economy in general. The main objective of the article is to document the sudden massive death of almond trees in the central High Atlas Mountains during 2022-2025. In March-August 2022, an average of 24.7% of dead trees was identified among the 4 074 almond trees in the study area. This average has increased to 88.2% in February-August 2024. In all the 17 studied fields, the average number of dead trees has risen rapidly in 2023. The results of monitoring almond trees in the field showed that tree mortality occurred mainly between March 2023 and July 2023, and that since September 2023, 88.2% of trees became totally dead. In the study area, almond trees play very important economic and ecological roles. Therefore, it is necessary to quickly find solutions to protect the remaining almond trees, as well as to help farmers and residents to obtain knowledge, techniques and funding necessary to carry out a regional campaign to plant almond trees in areas where trees have died. Keywords: Almond decline, tree mortality, Morocco, Drough

Artificial intelligence for enhancing supply chain management in agribusiness

The global agribusiness industry faces increasing complexity and challenges in supply chain management (SCM). These challenges arise from volatile market demands, environmental unpredictability and the necessity to ensure sustainability. Artificial Intelligence (AI) has emerged as a transformative technology to enhance SCM through advanced analytics, real-time decision-making and optimization. This review explores recent advancements in AI applications for agribusiness SCM, highlighting their theoretical and conceptual foundations. The discussion emphasizes AI's role in demand forecasting, logistics optimization, risk mitigation and sustainability. Policy implications and recommendations for integrating AI into agribusiness SCM conclude the paper, offering pathways for maximizing its potential. Keywords: AI, Agribusiness, Supply chain, Managemen

Agri-Fintech solutions for youth: Developing financial products tailored for young Nigerian farmers

Access to finance remains a critical barrier for young Nigerian farmers, despite agriculture being a pivotal sector for job creation and food security. Agri-fintech—the intersection of agriculture and financial technology—has emerged as a transformative avenue for delivering customized financial products to this demographic. This research review explores the landscape of agri-fintech innovations tailored for young farmers in Nigeria, assesses the suitability of current financial products, examines theoretical and conceptual models underpinning youth engagement in agri-finance, and synthesizes empirical findings from recent studies. Key themes include mobile lending, blockchain-enabled supply chains, micro-insurance, and digital savings. The paper concludes with policy implications for youth-centric agri-fintech design, financial inclusion, and sustainable agricultural development. Keywords: Agri-fintech, Youth, Innovation, Development, Nigeria, Rura

Trait correlation and heritability analysis in diverse upland rice (Oryza sativa) genotypes

This study evaluated agronomic traits' performance, correlation, and heritability in ten rice (Oryza sativa L.) genotypes grown at the Teaching and Research Farm of Federal University Dutse during the 2024 rainy season. The experiment followed a randomized complete block design with three replications. Analysis of variance revealed significant differences (p < 0.01) among genotypes for most traits, indicating substantial genetic variability. FARO 44 exhibited the highest grain yield per hill (145.3 g), followed by FARO 16 (138.6 g) and FARO 52 (140.7 g), while FARO 47 recorded the lowest yield (103.5 g). Days to heading (DTH) and days to flowering (DTF) showed high broad-sense heritability (99.9%), along with floret per panicle (99.6%) and grain yield per hill (98.5%), suggesting strong genetic influence. However, panicle length (59.4%) and fertility percentage (55.5%) had moderate heritability, implying environmental effects. Correlation analysis revealed a strong positive association between DTH and DTF (r = 0.970**) and between plant height and tillers per hill (r = 0.610**). However, plant height negatively correlated with DTH (r = -0.430*) and DTF (r = -0.405*), while grain yield exhibited weak associations with most traits. These findings highlight the potential for selecting high-yielding genotypes based on traits with strong heritability, particularly floret per panicle and grain yield per hill. The results provide useful insights for breeding programs aimed at improving rice productivity under similar agroecological conditions. Keywords: Upland rice, trait heritability, yield, days to heading, days to flowering, Nigeri

Mechanization and Extension Services in the Era of Buharinomics: Myth or Momentum?

The Buhari administration (2015–2023) in Nigeria introduced a suite of agricultural reform policies aimed at revitalizing the sector, with particular emphasis on mechanization and extension services. This paper critically reviews the implementation and outcomes of these policies within the framework of “Buharinomics”—the economic philosophy associated with President Muhammadu Buhari, assessing whether these initiatives constituted genuine developmental momentum or were largely rhetorical. Drawing on policy documents, national agricultural transformation plans, budgetary allocations, and empirical studies, the paper investigates the scope, scale, and impact of government-led mechanization drives and the revitalization of agricultural extension systems. While the era witnessed policy pronouncements and some structural investments—such as partnerships with foreign equipment suppliers and the deployment of extension agents—implementation gaps, inadequate funding, and bureaucratic inertia limited the overall effectiveness of these programs. The analysis suggests that despite notable initiatives like the Green Imperative Program and the National Agricultural Extension and Advisory Services Strategy, many promises remained under-delivered, reflecting a disconnect between ambition and execution. The paper concludes that while there was clear policy intent, the Buhari era's achievements in mechanization and extension were more myth than sustained momentum, necessitating a rethinking of institutional frameworks and accountability mechanisms in future interventions. Keywords: Agriculture, Advisory services, Policy, Nigeri

Innovations in post-harvest disease detection: From molecular diagnostics to AI-based imaging

Post-harvest diseases are a major contributor to global food losses, accounting for 20-50% of perishable crops, thereby threatening food security and economic stability. Traditional disease detection methods, such as visual inspection and microbiological culturing, are often slow, subjective, and lack the sensitivity needed for early pathogen identification. Recent advancements in biotechnology and computational analytics have introduced transformative solutions, including molecular diagnostics, spectroscopic techniques, and artificial intelligence-powered imaging systems. Molecular methods such as polymerase chain reaction, loop-mediated isothermal amplification, and CRISPR-based assays enable rapid and precise pathogen detection at the genetic level. Meanwhile, non-destructive technologies like near-infrared spectroscopy and hyperspectral imaging capture biochemical and morphological changes in produce, allowing for real-time monitoring. AI and machine learning further enhance these approaches by automating disease recognition through deep learning models such as convolutional neural networks, improving accuracy and scalability. This review comprehensively examines these innovations, discussing their principles, applications, advantages, and current limitations. Additionally, it explores future trends, including the integration of multi-modal detection systems and edge computing for on-site diagnostics. By leveraging these cutting-edge technologies, the agricultural sector can significantly reduce post-harvest losses, enhance food safety, and optimize supply chain efficiency. Keywords: polymerase chain reaction, loop-mediated isothermal amplification, CRISPR, hyperspectral imaging, near-infrared spectroscopy, artificial intelligence, machine learning, deep learning, convolutional neural networks, food security, pathogen detection, non-destructive testin

Women and carbon farming cooperatives: A model for climate-smart agriculture

The intersection of gender empowerment, cooperative farming, and climate resilience offers a promising model for sustainable agriculture. This review explores the role of women-led carbon farming cooperatives as a vehicle for promoting climate-smart agriculture (CSA). By synthesizing recent empirical studies and theoretical advancements, the article illustrates how gender-inclusive cooperative models contribute to soil carbon sequestration, climate resilience, and sustainable livelihoods. It underscores structural and institutional challenges while advocating for policy interventions that enhance women’s participation and leadership in CSA cooperatives. The review reveals that empowering women through cooperatives not only bridges gender gaps in agriculture but also accelerates the global transition to climate-resilient food systems. Keywords: Agriculture, Climate, Development, Gender, Resilience, Rural, Sustainabilit