Gomal Journal of Agriculture and Biology
Gomal Journal of Agriculture and Biology (GJAB) is a peer-reviewed academic journal published by GOMAL EDUCATION NETWORK (SMC-PRIVATE) LIMITED. The journal is dedicated to publishing high-quality research in agriculture and biological sciences, providing a platform for researchers, scientists, and academicians to share innovative findings with the global scientific community. Scope: The journal covers agronomy, crop and soil sciences, plant and animal sciences, biotechnology, microbiology, environmental sciences, sustainable agriculture, and related interdisciplinary research that supports food security, ecosystem sustainability, and scientific advancement.
GOMAL EDUCATION NETWORK (SMC-PRIVATE) LIMITED
SMART IRRIGATION SYSTEM FOR CLIMATE RESILIENT AGRICULTURE: A SYTEMATIC LITERATURE REVIEW
The water shortage has resulted in climate change and higher levels of climatic variability becoming a key issue in the sustainability and food security of the world. Smart irrigation tools have become a new form of combining the Internet of Things (IoT) technologies, wireless sensor-based networks, remote sensing and machine learning algorithms and streamlining the utilization of water resources and the climate resilience. The systematic review is a mixed-method synthesis of 156 peer-reviewed papers published between 2010 and 2025, which is based upon both bibliometric analysis and qualitative thematic synthesis in estimating the technological development, agronomic performance and obstacles to adoption. The indication of the bibliometric evidence is the geometric increase in the size of the research with the conceptual change of threshold-based automation to the artificial intelligence-based adaptive irrigation systems. Some machine learning models that are highly predictive in nature are the Random Forest, XGBoost, convolutional neural networks (CNNs) and long short-term memory (LSTM) networks whereby the predictive accuracy of the soil moisture is 97 percent in controlled environments. Multipurpose monitoring, which implies the use of ground sensors and satellite-based NDVI analysis, and UAV images, is more efficient in regard to identifying uniformity of irrigation ([?]91% accurateness). It is asserted in Agronomic data as 18- 35 per cent more water-efficient compared to traditional irrigation with little expense to the yield in stress-resistant crops and noticeable decrease in greenhouse gas emissions. Despite the better technology, cost, as regards to the economy, and the unavailability of the infrastructure system and inadequacy of the digital literacy also play a major role in causing large scale adoption, especially among the small holder farmers in the developing regions. The results lead to the urgency of the integrated, AI enhanced irrigation framework in the realization of water management sustainability and climate adaptive farming.
Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0
PRECISION AGRICULTURE TECHNOLOGIES FOR SUSTAINABLE CROP PRODUCTION: A SYSTEMATIC LITERATURE REVIEW
Background: The global agricultural sector faces unprecedented challenges in meeting food security demands while minimizing environmental degradation. Precision agriculture technologies (PATs) have emerged as a transformative approach to achieving sustainable crop production through site-specific management and resource optimization. Objective: This systematic literature review synthesizes current evidence on the application, effectiveness, and sustainability outcomes of precision agriculture technologies for crop production. Methods: Following PRISMA 2020 guidelines, a comprehensive search was conducted across five major databases (Scopus, Web of Science, PubMed, IEEE Xplore, and ScienceDirect) for studies published between 2015 and 2025. A total of 1,268 records were identified, of which 42 studies met the inclusion criteria. Quality assessment was performed using the modified Newcastle-Ottawa Scale. Results: The review reveals that precision agriculture technologies demonstrate significant potential for enhancing both economic and environmental sustainability. Variable rate technologies showed the strongest economic benefits (22.3% ROI increase), while remote sensing and IoT-based systems improved nitrogen use efficiency by 15.1% and reduced pesticide application by 12.8%. Key technologies include GPS guidance systems, unmanned aerial vehicles, sensor networks, and artificial intelligence-driven decision support systems. However, adoption barriers persist, particularly for smallholder farmers in developing regions. Conclusion: Precision agriculture technologies offer a viable pathway toward sustainable intensification of crop production. Future research should prioritize multi-scale technology integration, climate-resilient systems, and inclusive solutions addressing the needs of diverse farming contexts. Policy support and capacity building are essential for realizing the full potential of these technologies in achieving global food security and environmental sustainability goals.
GUT MICROBIOTA ALTERATIONS IN INFLAMMATORY BOWEL DISEASE: AN IMMUNOMICROBIAL APPROACH
IBD (inflammatory bowel disease) that encompasses both Crohn's disease and ulcerative colitis is increasingly becoming evident that it is a complex interaction between the gut microbiome and immune system. The paper has investigated gut microbiota changes in inflammatory bowel disease (IBD) through a systematic approach that includes metagenomic, immunological biomarker, and clinical phenotyping. The findings showed a severe disequilibrium of microbiota, characterized by a significant reduction of beneficial commensals, including Faecalibacterium prausnitzii and Bifidobacterium longum, and an increase in pro-inflammatory ones, including Escherichia coli (adherent-invasive strains) and Ruminococcus gnavus. Quantitative sequencing showed a decrease in the abundance of short-chain fatty acid (SCFA)-producing bacteria (45-60 percent) with a dramatic increase in the abundance of pathobionts (p < 0.01). The immunological analysis showed that there was an elevation of mucosal cytokines, such as IL-6, IL-17, and TNF-a, with a positive relationship with indices of dysbiosis (r = 0.72). Functional metagenomics also demonstrated that microbial metabolic pathways were not functioning efficiently such as those that produce butyrate and those that decompose tryptophan. These channels were closely connected with the extent of wickedness of the illness. All of the data indicate that it is not only the ecological balance in the gut that is disrupted by IBD-associated dysbiosis but also the process of mucosal immune activation, which leads to self-perpetuating inflammatory cycle. These findings highlight the importance of microbiota-immune interactions in the pathophysiology of IBD and also suggest the potential of microbiome-targeted therapy as an adjunctive measure in the regulation of the disease.
Copyright (c) 2025 Muhammad Arif (Author) https://creativecommons.org/licenses/by/4.0
ORGANIC AMENDMENTS MEDIATING SOIL MICROBIAL BIOMASS AND ENZYME DYNAMICS IN AN INCUBATION STUDY
Organic amendments are widely recognized for their role in improving soil fertility and microbial functioning. This study evaluated the effects of different organic amendments—farmyard manure (FYM), poultry manure (PM), compost, and green manure (GM)—on soil carbon and nitrogen pools, microbial biomass, and enzyme activities under incubation conditions at the Soil Physics Laboratory, ISES, University of Agriculture Faisalabad. Results indicated significant improvements in total organic carbon (TOC), total nitrogen (TN), microbial biomass carbon (MBC), and microbial biomass nitrogen (MBN) with all amendments compared to the unamended control. GM recorded the highest increases in TOC (11.9 g kg⁻¹), TN (0.95 g kg⁻¹), MBC (312 µg g⁻¹), and MBN (62 µg g⁻¹), followed closely by PM. Enzyme activities, including dehydrogenase, urease, phosphatase, and β-glucosidase, were also strongly enhanced, with GM and PM showing the most pronounced effects. These results underscore the potential of organic amendments in mediating soil biochemical processes and sustaining fertility. Adoption of labile, nutrient-rich amendments, particularly GM and PM, may provide effective strategies to enhance soil microbial functioning, nutrient cycling, and long-term sustainability of intensive cropping systems.
Copyright (c) 2025 Irfan Ahmad, Muhammad Bilal (Author) https://creativecommons.org/licenses/by/4.0
PHARMACOGENOMIC VARIABILITY IN CHEMOTHERAPEUTIC DRUG RESPONSE AMONG CANCER PATIENTS
The heterogeneity in pharmacogenomics plays a critical role in the modulation of the response of the chemotherapeutic drugs, both therapeutic efficacy and toxicity in cancer patients. This research was done using genome-wide and gene-specific polymorphisms in order to determine the level of correlation between them and interindividual differences in drug metabolism, treatment response and outcomes of adverse events in a heterogeneous group of cancer patients. The results showed that there were significant differences in key genes including CYP2D6, TPMT, DPYD, UGT1A1, and ABCB1, which altered the plasma drug levels, dose-limiting toxicity and progression-free survival significantly, and the p-values were always below 0.05. Carriers of reduced-function DPYD alleles proved to have much higher toxicity induced by fluoropyrimidine, and anti-UGT1A1 *28/*28 precursors showed a strong relationship with neutropenia induced by irinotecan. Moreover, there was a relationship between mutations in ABC transporters with varying levels of intracellular accumulation of drugs which affects the response rates of the platinum-based therapies. Polygenic risk modelling enhanced the fidelity of the treatment outcomes prediction by 28 which means that there is a high potential of integrated pharmacogenomic profiling in personalised oncology. All of the data collectively support the idea that genetic variation is significant in terms of chemotherapeutic response pathways and again underlines the need to have genomics-based dosage regimens so as to increase the therapeutic effect and reduce the toxicity effects in cancer patients.
Copyright (c) 2025 Nimra Samad, Muhammad Bilal (Author) https://creativecommons.org/licenses/by/4.0
GENETIC VARIABILITY AND TRAIT ASSOCIATIONS FOR YIELD AND FIBER QUALITY IN UPLAND COTTON (GOSSYPIUM HIRSUTUM L.)
The genetic advance of upland cotton requires a synchronized focus on both yield and fiber quality traits, as these features collectively conclude the crop’s economic value. The current study was piloted at the Cotton Research Section (CRS), Ayub Agricultural Research Institute (AARI), Faisalabad, to gauge 18 cotton genotypes for their agronomic performance and fiber quality. Yield components such as per plant bolls, boll mass, per plant seed cotton yield, seed index and ginning outturn (GOT %) displayed wide variability, with genotypes G6 and G16 recording the highest outcome traits. Traits of fiber excellence i.e., length, strength, micronaire, and uniformity ratio, also exhibited marked genotypic variation. Genotypes G6, G2, and G16 were superior in length (≥32 mm), strength (>30 g tex⁻¹), and uniformity (>85%), while maintaining acceptable micronaire values. The findings emphasize the role of genetic variability and trait associations in guiding cotton improvement strategies.
Copyright (c) 2025 Muhammad Shafique, Nimra Samad (Author) https://creativecommons.org/licenses/by/4.0
DETERMINANTS OF MALNUTRITION IN LOW-INCOME COMMUNITIES: A PUBLIC HEALTH PERSPECTIVE
Malnutrition remains a severe issue of the public health concern in low-income regions, where nutrition outcomes are imbalanced to present a complex interaction of socioeconomic, environmental, and behavioural issues. This study was based on the mixed-method approach, as the primary factors behind adult and child malnutrition in less-resource-rich environments were studied. Quantitative results indicated that elevated incidences of undernourishment were significantly associated (p < 0.05) with house hold food insecurity, low parental education, insufficient maternal nutrition, insufficient sanitation, and inadequate health service. The anthropometric measurements revealed that a proportion of 14 percent of the children was wasting, a proportion of 21 percent was underweight and proportion of 32 percent were stunted which showed chronic undernutrition in diet. Regression modelling revealed that the highest predictors of childhood nutritional status were mother education level, household income and frequency of healthcare utilisation (R2 = 0.71). She was supported by the quantitative findings of the study in which qualitative findings indicated an effect of barriers, which included insecure work, increasing food prices, cultural eating habits, and lack of knowledge about a healthy diet. The result of the combination of the two datasets is the realization that it is not the individual element but multifaceted deprivation that leads to hunger. The research is concluded on the general findings on the fact that to undertake the issue of malnutrition among the low-income neighborhoods, community-based, holistic approaches including infrastructure creation, maternal health, economic empowerment, and nutrition education are required. Such findings present evidence-based information to policy makers to develop long-term population health programs to reduce the incidence of malnutrition among the vulnerable populations.
Copyright (c) 2025 Naveed Hussain, Zahid Ali (Author) https://creativecommons.org/licenses/by/4.0
HYDROPONICS, AQUAPONICS, AND CONTROLLED-ENVIRONMENT AGRICULTURE AS INTEGRATED SOLUTIONS FOR FOOD SECURITY
This paper discusses hydroponics and aquaponics, and the controlled-environment agriculture (CEA) as unified approaches to enhance food security through boosting production, resource use, and sustainability. It employed a mixed-methods experimental design that combined controlled trials and stakeholder interviews. Quantitative information indicated that hydroponics had the highest production of crops, aquaponics increased protein by raising fish and a higher rate of recycling of nutrients, CEA ensured that crops were produced throughout the year even at higher energy consumption. Efficiency in the use of water and energy indicated that Hydroponics and aquaponics were significantly superior to conventional agriculture. CEA, in its turn, secured the weather changes. Qualitative results highlighted the differences in priorities of stakeholders: practitioners were focused on cost-effectiveness and scalability, whereas policymakers focused on the environmental impact and the resilience of the food system. A combined food security index (FSI) was developed which considers yield, water efficiency, energy efficiency and the way individuals perceive sustainability. Findings indicated that every system possesses advantages but a hybrid system that smartly incorporates hydroponics, aquaponics and CEA has the most likely of delivering food security in the long run. This research concludes that integrated agri-technological systems present a complex solution to the world food needs, environmental pressures as well as strengthening climate change resilience.
PHYTOREMEDIATION AND PLANT-MICROBE INTERACTIONS IN HEAVY METAL DETOXIFICATION
The environment continues to be in big trouble with heavy metal pollution particularly in formerly industrial areas. This paper explores a hybrid phytoremediation system that could apply the use of phytoremediation hyperaccumulator plants and beneficial soil bacteria to enhance the process of detoxifying cadmium (Cd), lead (Pb), arsenic (As) and zinc (Zn). The three types of plants namely Brassica juncea, Pteris vittata and populus deltoides were grown under controlled environments with and without microbial inoculants in the forms of phosphate solubilizing bacteria and mycorrhizal fungi. Their findings indicated that microbe treatments proved to be beneficial to a large extent in terms of metal uptake, biomass and chlorophyll conservation. The incidences of metal accumulation were more in shoot tissues and the qPCR tests indicated that there was an increased activity of metal transporter genes such as PCS1 and MT2. The statistical models revealed that the connection between microbial colonization and improved detoxifying parameters was adequate. This plant-microbe conjugation approach is a promising, long-term method of cleaning polluted soils containing heavy metals and it may also have significance in land rehabilitation and environmental biotechnology.
HYBRID IMAGING IN SYSTEMS NEUROSCIENCE: FROM CELLS TO CIRCUITS
New developments in hybrid imaging have made a revolution in systems neuroscience, permitting researchers to view cellular dynamics and circuit-level activity simultaneously. In this study a pair of two-photon calcium imaging, wide-field mesoscale recording and electrophysiological verification are combined with an aim to examine the forms of neuronal behaviour at various spatial and functional resolution. We took the transgenic mice in which the calcium indicators were genetically encoded to trace the activity of the neurons when the mice engaged in various activities and in various kinds of stimulation. Quantitative calculations revealed that the rate of spikes as well as the amplitude of calcium increased significantly when individuals got more excited and engaged in something. MEAN SP FREQUENCIES were greater than 8 Hz and the signals amplitudes were near 0.0 to 1.0 0.0. The calculation of functional correlations, which was done after signal synchronisation and behaviour indexing indicates that neural ensembles are coherent when they are active i.e. when moving. Scatter plots and hybrid overlays revealed sturdy correlations among spike actions and calcium indicators. This backs the opinion that optical imaging can be utilized as an electrophysiological substitute. In addition to that, the resemblance of the outcomes during all the nine sessions and the possibility to observe reoccurring neurological trends demonstrated that the situation was explosive and consistent. Behavioral state indexing allowed breaking down the responses of the brain into groups; thus, it demonstrated which subpopulations were processing information in the contextual manner. The patterns were complex though simple like dual-axes modulations and multimodal correlations in time-course and functional domains. These findings indicate the strength of hybrid imaging in recording the intricate connection between small-area neural activations as well as big-picture functional structure. The technology establishes a path to a decoding of neural computation that can be repeated and scaled, and teaches us some crucial details as to how the brain organizes its operations in real time. There are numerous potential applications it can have in the future: brain-machine interface, disease modeling, and mass neural mapping.
VETERINARY IMMUNOPATHOLOGY FOR PANDEMIC READINESS
An application of the science of veterinary immunopathology has been worthwhile in planning to contain pandemics since it enables us to decide how the immune system reacts to diseases of zoonotic nature and enables us to devise some early response methods. In light of the One Health paradigm, this paper examined immunopathological profiling, pathogen characterisations, and cross species disease monitoring in order to determine whether veterinary sciences can potentially be used to curb outbreaks. Through an integration of immunological and molecular analysis, we identified significant immune indicators showing the early exposure to pathogens. This will ensure that we identify pathogens within a short time and take the necessary action. The findings indicate that a comprehensive assessment of the veterinary immunopathology can enhance the development of the vaccines pipeline, aids in the treatment planning aspects, and enhances forecasting of the potential spillover outcomes. It is also found in the study that interdisciplinary cooperation is necessary, e.g., that veterinary experience should be combined with the existing public health structures to ensure a high level of outbreak response. The evidence incorporates the vital instrument of early warning systems and strategic judgement-making processes in times of new health concerns through addressing awareness and convergence of laboratory diagnostics, field epidemiology and the value of immunological representation. These data indicate that it is crucial to enhance veterinary diagnostic networks, promote the sharing of data in real-time and invest funds in the advanced immunopathological studies to reduce the risk of future pandemics. The conclusion of the study states that considering the long-term global health security, veterinary immunopathology should be undertaken in the preparation plans during any pandemic occurrence.
URBAN AGRICULTURE AND VERTICAL FARMING: HYBRID MODELS FOR FOOD PRODUCTION, RESOURCE EFFICIENCY, AND COMMUNITY HEALTH
This paper explores the hybrid approaches to urban agriculture that combine vertical farming and rooftop gardening to enhance food production, efficiency of resources, and health of communities living in urban areas. An experimental design was applied with mixed-method approaches to which both the quantitative and qualitative methods were applied. Experimental pilot hybrid systems were installed in certain metropolitan regions and compared to normal rooftop gardens under a control-treatment model. It was shown that using hybrid systems significantly improved yield per unit area, water-use efficiency (WUE), and energy-use efficiency (EUE), which were supported by ANOVA and regression modelling. Biomass production was shown to be more stable and resilient to hybrid systems, and possibly scaled in densely populated metropolitan settings. The results of the qualitative assessments by means of questionnaires and structured interviews highlighted positive community-level outcomes, including a greater dietary diversity, a better comprehension of the sustainable food habits, and a rise in wellness and health perception. Through triangulation to integrate quantitative performance indicators with qualitative data, we managed to obtain a complete picture of the role of hybrid urban agriculture. Findings indicate that these models are not only technologically effective, but also socially revolutionizing, providing a sustainable platform to address the issues of food hunger in cities, issues of the environment and community health. This study indicates that hybrid urban agriculture has substantial replication and policy incorporation capabilities in the creation of resilient urban cities in the future.
MACHINE LEARNING AND REMOTE SENSING INTEGRATION FOR EARLY DETECTION OF CROP DISEASES AND PEST OUTBREAKS
This study examines how machine learning algorithms can be used to combine with remote sensing technologies to detect agricultural diseases and insects infestations on a timely basis. Our mixed-method dataset consisted of an integration of multispectral and hyperspectral images with field data and farmer interviews (ground-truth data). The steps preceding it were the correction of the atmosphere, normalization of reflectance and extraction of features based on vegetation indices and texture measurements. Training and testing multiple machine learning models, including support vectors machine, gradient boosting, convolutional neural network, and random forest, were performed with a stratified k-fold cross-validation approach. These models demonstrated that they were able to give correct predictions with ROC-AUC values that were greater than the baseline values and F1-scores demonstrating that they were able to be able to detect damaged crops. The models were validated with field surveys and qualitative farmer feedback and ensured their usefulness in real-world applications in agriculture. The findings revealed that combination of both quantitative spectral attributes and qualitative observations reduced the rate of misclassifications and enabled the system to be more stable in the evolving environments. The integrated process reveals a scaling, sustainable, and adaptable approach to performing precision agriculture that will be capable of prompt reactions that can reduce agricultural wasteage and enable food security to be more robust. The findings indicate that machine learning and remote sensing may be combined to establish an alternate method of real-time monitoring of a disease and pests.
Copyright (c) 2024 https://creativecommons.org/licenses/by/4.0
DESIGNING THERAPEUTIC GARDENS FOR PHYSIOTHERAPY-BASED MENTAL HEALTH REHABILITATION
This research examines the effectiveness of garden incorporated physiotherapy in enhancing the physical and mental health in individuals with mild to moderate symptoms of depression and anxiety. In 6 weeks period, 40 individuals were randomly assigned into either garden-based physiotherapy group or traditional indoor physiotherapy group. This has been conducted with a mixed experiment design. Depression and anxiety were measured with a Beck Depression Inventory-II (BDI-II), a State-Trait Anxiety Inventory (STAI) and Perceived Stress Scale (PSS). Flexibility, Grip strength, and balance were also measured with the aid of functional mobility tests. The treatment group (therapeutic garden) showed a great reduction in the levels of depression (mean BDI-II score decreased 28.2 to 11.4), anxiety (mean STAI score decreased 51.8 to 27.5), and stress. Their control also improved on sit-and-reach flexibility (+5.6 cm), grip strength (+5.2 kg), balance time (+6.8 seconds). Oral feedback of qualitative interviews revealed that respondents experienced intense emotional and sensory responses to nature including being more motivated, relaxed and not so tired. Improvements in mental health relating well with gains in physical performance was favorable (r = 0.76). Such outcomes demonstrate the significance of the environmental design in the planning of the therapies. They suggest that nature-based rehabilitation environments can enhance clinical outcomes because they benefit the body and the mind. According to the research, the therapeutic gardens would be an effective method of enhancing physiotherapy in mental health rehabilitation with statistical support.
BIOPHYSICS AND CELL MOTILITY IN CANCER METASTASIS
The mechanobiology of cancer dissemination remains to be a topic of interest in the framework of giving better treatment opportunities. In this paper, the cell motility during metastasizing cancer is investigated with the perspective of quantitative modeling combined with mechanical profiling and imaging-based medical analysis. Studying the influence of substrate stiffness on the way cells move, we have examined metastatic breast (MDA-MB-231) and pancreatic (PANC-1) cancer cell lines. Experimental tests confirmed that, by stiffening the extracellular matrix (ECM), cell motility can be increased about 500 times (from 4nm/min to 1.5m/min), the time by which cells will remain in the same location can also be increased significantly (more than 50 minutes), and the force by which cells can move can also be enhanced (up to 120 nN). This indicates how a stiff microenvironment could assist cancer to spread. Persistent random walk model fits well in the process of cell movement in a specific manner as the parameters of velocity and persistence show strong correlation between replicates. Manipulating cytoskeletal components using ROCK and microtubule inhibitors decreased traction and elasticity and indicated that actomyosin contractility and microtubule stability were also essential to invasive motility. Correlation analysis and scatter graphs indicated the direct relationship between the traction force and cellular stiffness. Hybrid visualizations also indicated that velocity and persistence concomitantly rose under the circumstances of cell mechanical stimulation. These findings were confirmed by transcriptomic analysis identifying that cells grown in high-stiffness matrices had more EMT-related and adhesion-related genes present. The collective research provides firm indication that cells of metastatic cancer modify their directions of movement and material properties under the influence of mechanical stimuli in the environment. These findings indicate the extent to which it is necessary to pay attention to the mechanotransduction pathways when designing medicine that would prevent metastasis. Our experimental system is a system that can be re-used over and over to research the influence of mechanical forces on metastasis. It may be applied in drug screening and precision oncology.
VETERINARY CARDIOLOGY AND COMPARATIVE PHYSIOLOGY
This paper set itself the task of investigating the way in which cardiovascular physiology varies across species, as well as understanding how some of the more common veterinary species (primarily dogs, cats, horses, cows, birds, and marine mammals) respond physiologically to their environments. We collected quantitative data by using a mixed-method experimental study design, echocardiography, electrocardiography, haemodynamic and biomarker measurements. Qualitative clinical observations were also done seeing how the various species responded and what their morphological characteristics were. ANOVA, Pearson, and multivariate regressions, a statistical analysis, revealed large variance in the cardiac output, shape of the ventricles, conduction intervals and prevalence of valvular illness among the people. Equines were the specific animals with the highest cardiac output, birds had faster hearts and an enhanced oxygenation during cases of insufficient oxygen availability and marine mammals had an increased ratio of ventricular mass that allowed them to dive. These discrepancies were supported by graphical and tabular data that established the correlations between the functional performance and structural changes. Using both qualitative and quantitative data, we were in a position to see a complete picture of cardiovascular health of both species. The findings indicate that veterinary cardiology should have particular diagnostic reference values and that comparative physiology can be useful in clinical decision-making, preventive care strategies and assessing athletic performance.
CIRCULAR BIOECONOMY IN AGRICULTURE: VALORIZATION OF AGRICULTURAL WASTE INTO RENEWABLE ENERGY AND BIOPRODUCTS
The transition to a circular bioeconomy in agriculture must necessitate the new approaches to process and use agricultural wastes in a manner that is environmentally friendly. The research method employed a combined mix of qualitative and quantitative methods to experimentally determine the conversion of agricultural residues and livestock manure into renewable energy and bioproducts, and, at the same time, to estimate the perceptions of the stakeholders on the matter of feasibility and acceptability. Laboratory-scale work demonstrated that anaerobic digestion was applicable to producing biogas and thermochemical conversion was applicable to producing biochar. The findings indicated that the two processes have the potential to generate an abundance of methane and biochar that are both nutrient-rich and may enhance the soil fertility. Energy recovery efficiency calculations indicated that these technologies can be used as an alternative to fossil fuels that are renewable. Including the quantitative and qualitative data of the interviews with farmers and workshops with stakeholders revealed a great desire to make use of the waste-to-resource technology. But this aspiration was contained by the fact that there was a need to improve infrastructure, training and monetary rewards. According to the study, the transformation of agricultural waste into something that is useful is not only beneficial to the environment in terms of reducing greenhouse gases emissions and minimizing the amount of trash, it is also beneficial to the security of energy, the rejuvenation of soil, and the socio-economic development of rural areas. This study confirms the technical feasibility, environmental benefits, and social approval of waste valorization methods, and therefore, place circular bioeconomy models as the transformative methods of sustainable agriculture. The implications of the results are significant to policy makers and practitioners who would desire to accelerate the transition to more efficient and closed-loop agricultural systems.
SUSTAINABLE LIVESTOCK MANAGEMENT THROUGH GENOMICS, PRECISION FEEDING, AND ENVIRONMENTAL MONITORING
The present paper analyses sustainable cattle management through the composite method that combines genomics, precision feeding, and environmental monitoring. Genomic studies on whole-genome sequencing and genome-wide association studies have identified hereditary traits related to feed efficiency, milk supply and disease resistance, and heritability estimates support selective breeding programs. The precision feeding experiments, which were planned according to the randomized block designs and sensors relying on the Internet of Things, demonstrated significant improvements in the feed ratio and weight gain, a reduction in the level of methane emissions and feed expenses. Meanwhile, environmental monitoring sensors operating in real-time received alterations in temperature, humidity, and emissions, and demonstrated a direct correlation between ecological stressors and animal performance. Spatial mapping also demonstrated how pressure of grazing affects the sustainability of the environment. The qualitative interviews of farmers and livestock managers provided additional information regarding adoption barriers, socio-cultural attitudes, and the usefulness of the application of genomic and precision technologies to real-life situations. This overlapping of quantitative and qualitative information confirmed that sustainable livestock production requires both high-tech genetic and nutritional optimization and a strong correspondence with the experience of the farmers and with ecological reality. The findings indicate that, integrated systems are capable of enhancing production, reducing environmental impact, and enabling socio-economic resilience simultaneously, which make cattle more sustainable.
NUTRITIONAL AND MOLECULAR BENEFITS OF INDIGENOUS PLANTS IN TREATING VETERINARY SKIN CONDITIONS
This paper examines the effectiveness of four herbal extracts Azadirachta indica, Aloe vera, Calendula officinalis and Curcuma longa in the curing of skin issues in farm animals by considering their nutritional and molecular implication. Topical formulation was studied with mixed- methods experimental design comprising of Nutritional profiling, phytochemical quantification, clinical wound healing trials, hematological analysis, histopathology, and gene expression research methodologies. The findings demonstrated that all the plant-based remedies accelerated wound closure by up to 90 percent, reduced healing time to as minimal as 8 days and returned the hemoglobin in addition to white blood cells level to normal. Curcuma longa was found to have maximum molecular reaction. It activated the key regeneration genes such as VEGF and COL1A1 and switched off pro-inflammatory TNF-alpha. Phytochemical research has established that the level of phenolic and flavonoids plants increase in the capacity in which wound healing takes place on a plant, and the expression of genes.
MARINE BIOLOGY AND MOLECULAR ECOLOGY: CORAL RESILIENCE TO CLIMATE CHANGE
Coral reefs are increasingly threatened by climate-induced stressors such as ocean warming and acidification, necessitating a deeper understanding of species-specific resilience mechanisms. This study investigates the physiological and molecular responses of three reef-building coral species—Acropora millepora, Pocillopora damicornis, and Porites lobata—under simulated climate stress conditions. A mixed-methods experimental framework was applied, combining field-based sampling, controlled thermal and pH stress assays, and high-throughput RNA sequencing to assess photochemical efficiency (Fv/Fm), symbiont density, chlorophyll a concentration, and transcriptional resilience indices (TRI). A total of 180 samples across nine treatment sets were analyzed. Results revealed that P. lobata demonstrated superior physiological stability and the lowest TRI values (<1.0), indicating strong transcriptional robustness under stress. In contrast, P. damicornis exhibited significant declines in Fv/Fm and symbiont density, coupled with high TRI values (>2.0), reflecting pronounced transcriptomic disruption. A. millepora presented moderate resilience, with variable outcomes across replicates. Functional enrichment of differentially expressed genes implicated oxidative stress response, apoptosis regulation, and symbiont-host communication as key processes underpinning resilience. Complex visualizations including hybrid box-strip plots and interaction heatmaps confirmed interspecies differences and validated TRI as a predictive metric. The findings were further reinforced by ecological expert feedback, which aligned with model predictions. Overall, this study identifies P. lobata as a climate-resilient coral species and presents a replicable framework for evaluating coral stress responses using integrative molecular and ecological metrics. The approach has broad implications for reef conservation, restoration planning, and adaptive management under ongoing climate change.
REHABILITATION MEDICINE FOR AVIAN ORTHOPEDIC INJURIES
This paper examines the bird orthopaedic injury rehabilitation medicine approaches and makes a comparison of the findings of the nine different sets of data that exceeded twenty cases each. We focused our information in five species which are important and these are; parrots, hawks, falcons, eagles, and owls. These were their age, weight, kind of injury, the duration of treatment, recovery score and the follow-up outcome. It was statistically significant that younger birds had higher recovery scores and that larger species, specifically eagles required more time to rehabilitate. The most prevalent type of injury was fractures and they took longer to heal whereas sprains had faster healing spans. Referring to multimodal approach to treatment, in particular, involving physiotherapy and nutritional supplementation, the outcomes of their successful recovery were improved. Splinting and physiotherapy produced the best full-recovery rates. How length of treatment, recovery score, age and type of injury was related was represented by 12 complex visualisations including bar, scatter, line, pie and hybrid plots. These reinforced the statistic findings. These findings demonstrate the necessity to use species-specific rehabilitation plans, initiate the treatment early, and offer careful follow-up care to achieve optimal functional recovery. These outcomes provide veterinarians, wildlife rehabbers and conservation organizations with ideas on how to better handle the health and survivability of birds in orthopaedic orthopaedic injury.
DIGITAL AGRICULTURE AND IOT-ENABLED SMART IRRIGATION SYSTEMS FOR WATER-EFFICIENT FARMING
New irrigation techniques are required due to the fact that fresh water sources are becoming depleted at a rapid rate and agriculture is required to generate greater food output with reduced water. This paper investigates how smart irrigation systems can be used to enhance water-use efficiency as an aspect of digital agriculture through IoT-enabled systems. Mixed-methods experimental design was employed to combine the quantitative field trials with qualitative response of the farmers. On test plots, we installed internet of things sensors of soil moisture, temperature, and flow. These sensors were relaying real time data to cloud-based solutions where mathematical equations of scheduling and machine learning were to make the most optimal irrigation choices. The findings revealed that intelligent irrigation systems reduced water consumption by as much as 30 percent and crop yields remained or even improved. This was demonstrated in increased ratios of water-use efficiency as compared to traditional approaches. Statistical analysis revealed significant variation across treatments, and crop growth observation supported the positive response of the physiological to precision irrigation. Also, the farmers interviewed reported increased usability, reduced labour needs and increased trust in automated systems. The qualitative and quantitative outcomes combined indicate that IoT-based irrigation is a major aspect of climate-smart agriculture. It could render the farming more resilient, sustainable, and productive.
AGROFORESTRY AND CARBON SEQUESTRATION: MULTIFUNCTIONAL LANDSCAPES FOR CLIMATE-SMART AGRICULTURE
Agro forestry has grown to be a multifunctional land-use practice that shows significant potential of carbon sequestration and climate resilient farming. This study employed a combination of mixed-methodological experimental designs, whereby field measurements, remote sensing, statistical modelling and qualitative assessment were used to investigate how the agro forestry systems would help in carbon sequestration and landscape sustainability. Randomized field trials were used to collect quantitative data on soil organic carbon, aboveground biomass and species richness in a number of agroecological zones. At the same time, semi-structured interviews and participatory rural evaluations were used to record farmer perceptions. The results revealed that agroforestry significantly enhanced carbon sequestration compared to monoculture systems and all measures of tree density and canopy cover were positively related to carbon storage. Regression and PCA analyses were used to identify key biological driving factors, and GIS-based spatial modelling was used to suggest that huge mitigation was possible with widespread adoption of agroforestry. Qualitative data showed that farmers valued agroforestry not only due to its environmental benefits but also due to its ability to diversify economic activities, to increase the resilience to weather unpredictability, and to improve food security. Ecological measurements coupled with socio-economic knowledge provided us with an overview of agroforestry as a land use method with numerous applications. This analysis concludes that agroforestry is a sustainable and climate-resistant approach to land management, which has the added advantage of capturing carbon, preserving biodiversity and enabling rural regions to develop. These findings are a strong indication that agroforestry development should be a policy objective towards climate change mitigation and sustainable agriculture.
Copyright (c) 2023 https://creativecommons.org/licenses/by/4.0
PHYTOCHEMICAL-RICH AGROFORESTRY SYSTEMS FOR SUSTAINABLE LIVESTOCK FEEDING
In this study, the researchers examine the possibility that high phytochemical agroforestry systems might be a long-term, healthy cattle feeding practice. We employed a mixed-methods experimental study to cultivate tree species, which are indicated to have high quantities of positive secondary metabolites like Moringa oleifera, Leucaena leucocephala, and Gliricidia sepium, under silvopastoral conditions. We analyzed the biomass of such systems to determine the nutrients and phytochemicals contained in them such as the total quantity of phenolic and flavonoid chemicals. In goats, feeding experiments demonstrated that animals fed the phytochemical-rich forages weighed more, retained more feed energy as energy, and improved their blood health compared with animals not eating these phytochemical-rich forages. There was an increase of hemoglobin, serum protein, and white blood cells in the experimental groups implying better immune system and metabolism rates. Grassroots agriculture also pondered on qualitative responses that confirmed how easy to use the system and how it was helping the environment through schemes like soil quality improvement and decreasing the application of synthetic materials. The relationship between phytochemical levels and health in animals was strong as indicated by statistical tests. The conclusion of the study is that the inclusion of phytochemical-rich agroforestry systems in the nutrition program of livestock has much potential in boosting the animal health, reducing the expenditure of feed, and environmental conservation. It is a climate-resilient and scalable approach to addressing the issues with the cattle nutrition, particularly in low-resource environments.
Copyright (c) 2023 Shahid Iqbal , Israruddin, Muhammad Asif (Author) https://creativecommons.org/licenses/by/4.0
COMPUTATIONAL BIOLOGY IN HOST-PATHOGEN INTERACTION PREDICTION
In the case of making discoveries on how to treat infections and understand their working mechanisms, the interaction between proteins of host and pathogen requires us to know how they interact with each other intricately. The present paper provides a full computational framework to predict a host-pathogen interaction (HPI) that involves functional annotation, structural bioinformatics, and machine learning. We used human host and key pathogen protein datasets (Salmonella enterica, SARS-CoV-2, Candida albicans) and trained known HPI datasets up to a group of classifiers, i.e., Support Vector Machines, Random Forest, and Gradient Boosting. We employed such characteristics as sequence similarity, domain-domain interaction and subcellular localization. There were nine different computer models that made 180 high-confidence HPIs. The consensus ensemble scoring was implemented to increase the likelihood of interactions. After that, we performed structural docking simulations with the highest-ranking pairs. The binding free energy calculated indicated that over 65 percent of the expected complexes possessed favorable 6G (< =8 kcal/mol) values, a fact that demonstrated the feasibility of the structures. The top contacts were demonstrated to be highly impacted with effector and immune modulator proteins based on functional analysis. Using measurements over networks, central hub proteins that are well connected were identified and may be good targets of therapy. All line plots, bar charts, scatter graphs, pie charts, and hybrid figures indicated that the same trends occurred in all functional annotations, docking confidence, and interaction probability. An Integration of the comments of experts on infectious diseases ensured that the computer calculations made biological sense, and could be well-understood. The findings indicate that computational biology is an effective method that can easily and speedily forecast HPI and may be utilised to test and apply on new illnesses in the future.
WILDLIFE TOXICOLOGY AND ENVIRONMENTAL CONTAMINANTS
This paper examined the prevalence of contaminants in the environment towards wildlife, their accumulation in their bodies, and influence in the ecosystem. It did this by utilizing field sampling, more lab investigations and stats modeling. To determine whether samples contained heavy metals, pesticides and microplastics, we investigated samples of a diverse mix of aqueous and terrestrial species. We also in situ checked water quality. The findings indicated the prediction of trophic magnification in the sense that the predators species contained more mercury, lead and cadmium. The number of pesticide residues was also massive, particularly in the agricultural buffer zones. Comparative analysis of seasonal fluctuation indicated that the wet seasons witnessed greater number of contaminants. Filter-feeding species were most contaminated with microplastics. Dose-response correlations between the levels of contamination and death, sublethal impacts, and reproduction issues came out to be high in controlled exposure experiments. Multivariate models of regression showed some crucial factors, which included depletion of dissolved oxygen, nutritional enrichment, and pollution load, as factors, which predicted toxicity. The research indicates the interaction that exists between chemical pollutants and the environment surrounding the animals to influence their livelihood. This demonstrates the necessity to keep track of these factors as a whole unit and devise certain methods in minimizing their impact. These findings contribute to the growing amount of knowledge regarding the environmental hazards of environmental pollutants. They set a scientific foundation to rules and conservation strategies that aim at safeguarding the biodiversity and maintaining the oneness of the ecosystems.
HYBRID APPROACHES IN PLANT BREEDING: COMBINING GENOMICS, BIOTECHNOLOGY, AND TRADITIONAL KNOWLEDGE FOR GLOBAL FOOD SYSTEMS
This study explores an integrated approach in which genetics, biotechnology and traditional knowledge are combined to transform food production in the world through plant breeding approaches. Genomic sequencing, QTL mapping, and CRISPR-based assays with participatory ethnographic methodologies assisted us in discovering what farmers desired and how they bred plants. A randomized complete block study using field research across multiple seasons generated quantitative phenotypic data, which included yield, water-use efficiency, and indicators of stress tolerance. Application of the traditional knowledge as covariate in genotype environment interaction models displayed a significant correlation between attributes as indicated by the farmer and the heritability estimates that were statistically determined. State-of-the-art machine learning models, in particular XGBoost with SHAP-based interpretability, demonstrated high predictive capability and demonstrated interaction between genetic and cultural factors. Multivariate analysis (PCA and clustering) showed that there were unique genetic variation patterns which could be grouped with the varietal types as defined by the farmers. Cultural significance of specific qualities was also supported by thematic analysis of qualitative narratives and ensured that technological improvements did not become socially or ecologically detached. The combined results suggest that hybrid plant breeding strategies can significantly enhance the resilience, productivity, and flexibility of agriculture toward climate change and that such strategies will also guarantee an engagement and acceptance of farmers. This research presents a viable and replicable methodological approach that incorporates molecular science and traditional bodies of knowledge and therefore improving the world food security and sustainability.
ADVANCING SOIL HEALTH AND CLIMATE RESILIENCE THROUGH AGROECOLOGICAL PRACTICES AND SMART FARMING TECHNOLOGIES
This study will analyze how agroecological practices combined with smart technologies of farming can improve soil health and climate resilience. Field trials explored interventions which included cover cropping, mulching, crop rotation and precision irrigation using a mixed-method experimental design. IoT-based sensors and AI-driven decision support were in support of these. Quantitative analyses were done on soil organic carbon, the levels of nitrogen, the biomass of the microorganisms, the rate of infiltration, and the measurements of climatic resilience, including water retention and the and stability of the yields. The data were analysed via statistical testing, predictive modelling and Monte Carlo simulations. Qualitative insights were obtained through Farmer questionnaires and focus group talks. The results showed that agroecological practices significantly enhanced the soil fertility, water retention and microbial activity, and smart technology significantly enhanced efficiency in irrigation and nutrient management. The predictive models revealed that combined methods are robust to operate in numerous weather conditions. They have the ability to cushion against variation in rainfall and maintain yields. The farmers claimed they would employ sustainable methods more when they had access to technology and participatory structures. The joint study revealed that the application of digital tools and ecological knowledge provides synergistic benefits and the environment, as well as the economy, are enhanced. These findings demonstrate that agroecological-smart farming techniques could be applied on a bigger scale to make food production more sustainable and assist people in adjusting to climate change.
EPIGENETIC MODULATION IN MEDICINAL PLANTS AND ITS APPLICATIONS IN ANIMAL HEALTHCARE
Epigenetic regulation plays a pivotal role in modulating the biosynthetic pathways of secondary metabolites in medicinal plants. This study investigates the relationship between DNA methylation, histone acetylation, gene expression, and bioactive compound production in twenty medicinal plant species with known veterinary relevance. Utilizing a mixed-methods experimental framework, we employed bisulfite sequencing, ChIP-qPCR, and qRT-PCR to profile epigenetic marks and gene expression, alongside LC-MS/MS for metabolite quantification. Our results revealed a strong inverse correlation between DNA methylation and gene expression (r = –0.78) and a positive correlation between histone acetylation and transcript abundance (r = 0.81). Species with low methylation and high acetylation exhibited significantly elevated expression of biosynthetic genes (e.g., PAL, CHS), accompanied by increased metabolite yields. In vivo trials on small ruminants demonstrated significant reductions in TNF-α and IL-6 levels and enhanced gut microbial diversity following extract administration. Statistical analyses, including ANOVA and multivariate regression, confirmed the therapeutic efficacy of these extracts. Additionally, qualitative insights from veterinary practitioners supported the clinical potential of these phytotherapeutics. Collectively, the findings emphasize the functional relevance of epigenetic modulation in medicinal plants and advocate its translational application in developing sustainable, evidence-based treatments for animal healthcare.
SYSTEMS BIOLOGY AND MOLECULAR PATHWAYS IN CHRONIC INFLAMMATION
Chronic inflammation has become one of significant contributors of complex illnesses yet the mechanism to this effect is not very clear at the molecular level. In this research, a mixed-method systems biology, which involves transcriptomics, proteomics and metabolomics, is utilized to determine what regulatory networks, as well as pathways changes are associated with chronic inflammatory diseases. Important inflammatory genes, including IL-6, TNF-a, NLRP3 and STAT3, are switched on as revealed by high-throughput RNA sequencing. It was observed that the protein expression also increased as analyzed by ELISA and western blot. Metabolomic analysis identified gross alterations in the immunometabolic intermediates including succinate, lactate and arachidonic acid. This indicates that the body is shifting to pro-inflammatory energy metabolism. Principal component analysis and multi-modal hybrid plot succeeded in separating treatment group (treated), sick, and control groups remarkably well. This indicates which signatures of omics are robust and reefficient. Further, time-resolved expression analysis revealed that cytokine activity decreased in response to treatment, which indicates that the pathway was most likely blocked throughout the duration of study. The persistence of this disease was associated with pathway enrichment, network centrality analysis, and experimental verification of involvement of NF- 0 B, JAK- STAT, and NLRP3 inflammasome pathways. The findings can be used to describe the chronic inflammation mechanism and identify certain molecular targets that could be deployed in diagnostics and therapy. This is the demonstration of the capability of multi-layered systems biology to decipher complex immune system issues and advance precision medicine.