Journal of Poultry Sciences and Avian Diseases

The poultry industry is increasingly seeking nutritional strategies that enhance productivity, support intestinal health, and reduce reliance on antibiotic growth promoters. However, many functional feed additives, including vitamins, organic acids, essential oils, probiotics, enzymes, and trace minerals, are susceptible to degradation during feed processing, storage, and gastrointestinal transit, which can limit their stability, bioavailability, and biological efficacy. Encapsulation technologies have emerged as effective delivery approaches to address these limitations by protecting bioactive compounds and enabling controlled or site-specific release within the digestive tract. This mini-review summarizes recent advances in encapsulation-based delivery systems for poultry nutrition, with emphasis on microencapsulation, nanoemulsions, spray-dried formulations, and controlled-release platforms. Available evidence suggests that encapsulated feed additives can improve nutrient stability, enhance intestinal availability, support epithelial barrier integrity, modulate gut microbiota, and contribute to improved growth performance and feed efficiency. Encapsulated phytogenics, organic acids, probiotics, enzymes, and nano-formulated minerals also show potential as components of antibiotic-reduction strategies in modern poultry production. Nevertheless, challenges related to manufacturing scalability, cost-effectiveness, regulatory approval, formulation standardization, and long-term safety remain important barriers to wider commercial adoption. Future research should focus on optimizing carrier materials, improving release precision, validating efficacy under commercial production conditions, and integrating encapsulation technologies with precision nutrition strategies. Overall, encapsulation represents a promising approach for improving the efficacy of functional feed additives and supporting sustainable poultry production in the post-antibiotic era

Neuropeptide W (NPW) is an endogenous ligand for GPR7 and GPR8 receptors and has recently been identified as an orexigenic factor in birds. However, the involvement of the central opioidergic system in NPW-induced feeding has not been investigated. This study aimed to determine the role of μ-, δ-, and κ-opioid receptors in hyperphagia elicited by intracerebroventricular (ICV) injection of NPW23 in neonatal broiler chicks. A total of 176 male chicks (Ross 308 strain), aged 24 hours post‑hatching, were utilized as experimental subjects across four distinct investigations. In Experiment 1, chicks received ICV injections of control solution or NPW23 (0.75, 1.5, and 3 nmol) to establish a dose-response curve. In the second experiment, subjects received injections of either a control vehicle, NPW23 at a dosage of 3 nanomoles, β-funaltrexamine (β-FNA; a selective μ-opioid receptor antagonist), or a combination of NPW23 and β-FNA. The third experimental trial employed naltrindole (NTI; a δ-opioid receptor antagonist), whereas the fourth investigation utilized nor-binaltorphimine (nor-BNI; a κ-opioid receptor antagonist). Following treatment administration, cumulative feed consumption was measured at 30, 60, and 120 minutes post-injection and subsequently normalized to each subject’s body weight. NPW23 at 1.5 and 3 nmol dose-dependently increased food intake at all time points (P < 0.05). Co-administration of β-FNA with NPW23 significantly potentiated NPW23-induced hyperphagia (P < 0.05). In contrast, co-injection of NTI or nor-BNI with NPW23 did not alter the orexigenic response (P ≥ 0.05). These findings indicate that μ-opioid receptor blockade potentiates NPW23-induced feeding, suggesting that central μ-opioid receptor signaling may exert an inhibitory modulatory influence on NPW23-induced hyperphagia in neonatal broiler chicks.

Apelin-13, a bioactive peptide acting via the G protein-coupled receptor APJ, has recently emerged as a potential anorexigenic factor in vertebrates. However, the central neural pathways recruited by apelin-13 to suppress appetite in birds remain largely elusive. This study investigated the involvement of central adrenergic receptor subtypes (α₁, α₂, β₁, β₂, and β₃) in apelin-13-induced hypophagia in neonatal broiler chicks. In a series of six experiments, 3-hour food-deprived Ross 308 chicks (n=11 per group) received intracerebroventricular (ICV) injections of apelin-13 (0.25, 0.5, or 1 µg) alone or in combination with selective adrenergic antagonists (prazosin, yohimbine, metoprolol, ICI 118,551, or SR 59230R). Post‑injection food intake (30, 60, 120 min) was measured and expressed as % body weight. Apelin-13 significantly reduced cumulative food intake in a dose-dependent manner, demonstrating a hypophagic effect (P < 0.05). Co-infusion of the selective β₂-adrenergic antagonist ICI 118,551 completely blocked apelin-13-induced hypophagia at all time points (P < 0.05). In contrast, antagonists of α₁, α₂, β₁, and β₃ receptors failed to alter apelin-13's anorexigenic action (P ≥ 0.05). The present study demonstrates that central administration of apelin-13 exerts a dose-dependent hypophagic effect in neonatal broiler chicks, which is specifically mediated by β₂-adrenergic receptors.

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Scientific journals do more than publish manuscripts. At their best, they help shape research priorities, strengthen methodological standards, promote ethical scholarship, encourage scientific dialogue, and support the translation of evidence into practice. As the Journal of Poultry Sciences and Avian Diseases (JPSAD) enters a new stage of international visibility, including its indexing in Scopus, it is important to reflect on both the opportunities and responsibilities that accompany this progress.
Poultry and avian health research is becoming increasingly multidisciplinary. Disease outbreaks, antimicrobial resistance, vaccination strategies, biosecurity, environmental conditions, flock management, nutrition, animal welfare, production efficiency, food safety, and public health are no longer isolated areas of study. They are interconnected components of a larger biological, veterinary, environmental, and societal system. This reality requires research that is not only technically sound, but also contextually meaningful, ethically responsible, and practically relevant.

Artificial intelligence (AI), machine learning, computer vision, sensor-based systems, and Internet of Things (IoT) technologies are increasingly used for automated monitoring of poultry health and welfare, but reported model performance varies across tasks, data sources, validation strategies, and production settings. This systematic review and meta-analysis evaluated the reported performance of AI-based models for poultry health and welfare monitoring. PubMed/MEDLINE, Scopus, and Web of Science were searched for peer-reviewed studies involving poultry, reporting health- or welfare-related monitoring outcomes, and providing extractable model-performance data. Data were extracted independently by two reviewers, and pooled accuracy was estimated using a Restricted Maximum Likelihood random-effects model in STATA version 17. Twenty-one studies published between 2012 and 2025 were included, of which ten were eligible for meta-analysis. Included systems used convolutional neural networks, random forests, support vector machines, and other machine-learning approaches for behavior recognition, disease detection, lesion assessment, mortality detection, environmental monitoring, and welfare assessment. The pooled accuracy estimate was 90.39% (95% confidence interval: 84.89–95.89; P < 0.001), with substantial heterogeneity among studies. Reported performance varied by application domain, data source, model type, assessment dimension, sample size, and integration with IoT-based systems. AI-based technologies show promise for automated poultry health and welfare monitoring; however, heterogeneous methods and limited external validation restrict the generalizability of pooled estimates. Future studies should prioritize standardized reporting, open datasets, external validation, and testing under commercial farm conditions.

The poultry industry is a critical reservoir of antimicrobial-resistant bacteria, with Escherichia coli and Salmonella sp. as major disease-causing organisms that disseminate high-priority resistance genes into the food chain. This case report details the molecular detection and characterization of plasmid-mediated quinolone resistance (PMQR), carbapenemase, and extended-spectrum β-lactamase (ESBL) genes in isolates of multidrug-resistant E. coli and Salmonella sp. obtained from a broiler breeder farm in Ibadan, Oyo State, Nigeria. Post-mortem examination was conducted on 12 broiler breeders presenting with septicemia. One representative Escherichia coli isolate and one Salmonella sp. isolate from pooled liver, kidney, and gallbladder samples with obvious gross post-mortem lesions were identified based on colony morphology on differential media (MacConkey agar), Gram’s reaction, and biochemical tests using the Analytical Profile Index. The isolates were tested for susceptibility to antibacterial agents with the Kirby-Bauer method. The isolates were also screened for ESBL (blaSHV, blaTEM, blaOXA-1, blaCTX-M), carbapenemase (blaNDM, blaKPC, blaIMP), and PMQR (qnrA, qnrB, qnrS) genes using PCR. The E. coli and Salmonella sp. isolates were resistant to all 12 tested antibiotics across six classes. The E. coli isolate had the blaTEM, blaOXA-1, blaNDM, qnrA, and qnrS genes; the Salmonella sp. isolate carried blaOXA-1 and qnrS. This report confirms that poultry serve as a reservoir for bacteria co-harboring critical ESBL, carbapenemase, and PMQR genes, thereby exhibiting severe multidrug resistance. The findings point to a serious public health concern and underscore the need for improved antimicrobial stewardship and surveillance in the food animal industries.

Chronic cyclic heat-stress conditions can challenge productive performance and physiological balance in broiler breeder hens, particularly during the laying period. The present experiment evaluated dietary curcumin and Protexin, a multi-strain probiotic, alone or in combination, in Arbor Acres broiler breeder hens from 22 to 35 weeks of age. Three hundred hens were assigned to five treatments with four replicate cages per treatment and 15 hens per cage: thermoneutral control, heat-stress control, heat stress + curcumin at 150 mg/kg feed, heat stress + Protexin at 50 g/ton feed, and heat stress + curcumin + Protexin. The thermoneutral group was maintained at 18–24°C, whereas heat-stress groups were subjected to 34°C for 6 h/day. The cage was considered the experimental unit. Egg production and settable egg percentage, defined as externally normal and crack-free eggs, were recorded daily, and egg-quality traits and blood variables were measured at 35 weeks of age. Compared with the heat-stress control, the combined-supplement group increased egg production from 64.95% to 70.87% and settable egg percentage from 63.91% to 68.11%. However, egg weight decreased from 66.98 to 62.89 g. The combined-supplement group also showed greater eggshell thickness, lower serum triglycerides and aspartate aminotransferase activity, higher estradiol and progesterone concentrations, and a lower heterophil-to-lymphocyte ratio. Interleukin-1β was not significantly affected. Overall, dietary curcumin and Protexin improved selected indicators of productivity, eggshell quality, metabolism, endocrine function, and stress response under the present cyclic heat-stress conditions, with the combined treatment showing favorable responses across several endpoints.

H5N1, or highly pathogenic avian influenza, continues to pose a serious risk to public health and poultry. In order to differentiate H5N1-infected from healthy chicken samples and to guide the development of diagnostics and vaccines, we postulated that Machine Learning (ML) applied to RNA sequencing (RNA-Seq) data could detect biologically meaningful immune gene signatures. While ML has been applied to other avian RNA-Seq datasets, to our knowledge, this study represents one of the first applications of interpretable ML to chicken H5N1 RNA-Seq transcriptomic data for immune signature discovery.

RNA-Seq data from H5N1-infected chicken lung and ileum tissues (ArrayExpress E-MTAB-2908) that were publicly available, were chosen. Fivefold stratified cross-validation (~80/20 train/test per fold) was used to train two supervised ML models, such as Random Forest (RF) and linear-kernel Support Vector Machine (SVM). Performance was evaluated using Area Under Curve (AUC) and Receiver Operating Characteristic (ROC) curves.

RF reached a mean AUC = 0.85, while SVM-Linear achieved AUC = 0.75. Top-ranking interferon-stimulated genes (ISGs), including IFIT5, MX1, and OASL, were consistently upregulated in infected samples, indicating activation of type I interferon pathways. Concordant findings across models support the stability and biological relevance of the identified signatures despite the modest sample size.

These genes are highlighted as potential candidates for early molecular diagnostics and for tracking vaccine-induced antiviral immunity. These findings broaden the methodological applications of interpretable ML in avian transcriptomics and computational immunology.