Horizon e-Publishing Group (HePG): E-Journals
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Potential of organic seed priming for improved crop productivity and sustainable agricultural development
Full text linkClimate change is a major global concern that adversely affects seedling emergence and crop development during critical growth stages. Thus, as a preventive measure and short-term strategy, seed priming is performed to boost germination and early growth of plants. Chemical seed priming has drawbacks, including high cost, selectivity and impact on target species, soil contamination and environmental pollution. Although plant genetic engineering, has advanced significantly developing resistant varieties remains a slow and unpredictable process. Technological advancements have created a path for future research on the improvement of current environment friendly seed enhancement methods with assured enhancement in seed vigour and crop productivity. Hence, organic seed priming serves as substitute due to their socioeconomic benefits and environmental safety. It represents an agro-ecological approach grounded in the principles of self-sufficiency, biodiversity, recycling and reduced dependency on chemical inputs. Soon, the organic seed priming is expected to exhibit fastest growth in the seed industry, partly due to its ease of registration with the environment regulatory agencies. Therefore, this reviews a few highlights preferred organic seed priming techniques, recent advancements and their significance in sustainable agriculture
Phytochemical analysis and in vitro antileishmanial activity of Basella alba extract cultivated in Iraq
No full textBasella alba, widely known as Malabar spinach, is a fast-growing perennial native to tropical regions Worldwide. B. alba has been widely utilized in traditional medicine because of anti-inflammatory properties, laxative, diuretic and antioxidant properties. The current research focuses on determining the chemical composition of B. alba and evaluating its antileishmanial efficacy against the promastigote of Leishmania tropica in vitro. This study is the first to examine the potential of B. alba as a natural remedy for leishmaniasis, as its antileishmanial properties have not been previously investigated. A Soxhlet apparatus was used to obtain whole-plant extracts of B. alba. The MTT proliferation assay was employed to evaluate the in vitro antileishmanial efficacy of L. tropica promastigotes. Reverse phase-high -performance liquid chromatography (RP-HPLC) was utilized to identify and isolate lupeol and β-sitosterol in the petroleum ether fraction. Gas chromatography-mass spectrometry (GC-MS) was employed to perform a comprehensive chemical profile of the fraction. To confirm the isolated compounds\u27 molecular structure and fragmentation patterns, structural characterization was performed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). To determine whether characteristic groups were found, Fourier-transform infrared spectroscopy (FTIR) was employed. The petroleum ether extract demonstrated dose-dependent anti-promastigote activity with a notable inhibition rate of 72 %, indicating its potential antileishmanial activity. The presence of bioactive components with established antileishmanial properties highlights the potential of B. alba as a natural antileishmanial agent. Further in vivo studies are needed to support these in vitro findings and confirm their therapeutic potential
Unveiling the antioxidant potential of Curcuma amada Roxb. leaf essential oil : An in silico and in vitro investigation of major constituents
Full text linkElevated levels of human peroxiredoxin 5 (Prdx5), a cytoprotective antioxidant enzyme protects cellular compartments from oxidative damage induced by peroxides. In recent years, essential oils are regarded a viable source of non-toxic antioxidant substances with a higher safety profile. Curcuma species have been shown to inhibit lipid peroxidation levels and enhance antioxidant enzyme activities. Thus, the present study was designed to screen potential antioxidant agents from C. amada leaf essential oil (CALEO) to interact and support the Prdx5 enzyme activity using in vitro and computational approaches. The essential oil obtained from was chemically characterised using GC-MS. The analysis identified 36 constituents with camphor (17.51 %), spathulenol (12.00 %) and curdione (10.27 %) as the major constituents of CALEO. Moreover, the antioxidant effects of the oil were evaluated using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2’-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS ) free radical scavenging assays, in which it demonstrated high DPPH (IC50 = 6.91 ± 0.04 μg/mL) and ABTS (IC50 = 5.86 ± 0.06 μg/mL) radical scavenging effects as compared to positive control. Subsequently, molecular docking analysis wascarried out between the key compounds of CALEO and Prdx5 protein. Amongst all, β caryophyllene, germacrone and ar -turmerone exhibited strong binding affinity (< -5.8 kcal/mol) against Prdx5 as compared to ascorbic acid (-5.3 kcal/mol). Furthermore, molecular dynamicsparameters such as RMSD (root mean square deviation), RMSF (root mean square fluctuation), Rg (radius of gyration), solvent accessible surface area (SASA), secondary structure and intermolecular H-bond plotted for the top scoring docked molecules indicated stability andminimal fluctuations over a 100 ns simulation period. Molecular mechanics poisson-boltzmann surface area (MM/PBSA) analysis revealed that Vander Waals interactions were the major contributor for stabilizing the complexes. Additionally, chemical absorption distributionmetabolism- excretion-toxicity (ADMET) analysis was conducted that revealed favourable pharmacokinetic and toxicity profiles for the lead compounds. Density functional theory (DFT) analysis was performed to investigate global reactivity parameters including MEP (molecular electrostatic potential), ELF (electron localization function), LOL (local orbital locator) and NCI-RDG (non-covalent interactions-reduced density gradient) for β-caryophyllene, germacrone, ar-turmerone and ascorbic acid. Ar-turmerone and germacrone displayed a small energy gap and higher reactivity compared to ascorbic acid. These findings suggest that germacrone and ar-turmerone may serve as promising novel antioxidant agents
Economic and environmental impact of drone technology in Indian agriculture: An overview
Full text linkDrones or small unmanned aerial vehicles, present a variety of opportunities for the agricultural industry. Drones are widely utilized for real-time airborne photography, sensor data collecting, pesticide spraying, soil analysis and fertilisation and animal monitoring in agriculture. Drones for agricultural spraying are being actively promoted by the Indian federal government. The main goals of these "Kisan drones" are to reduce spraying times, improve the effectiveness and efficiency of using resources for agricultural applications (pesticides, etc.) and lessen the negative health impacts of manually applying pesticides. Drones are anticipated to have a future role in aerial imaging, surveying and transportation in farming. This study shows that the state is actively promoting a more liberalized drone-friendly policy and offering large financial incentives to businesses, groups and specific farmers to buy, use or manufacture drones as needed. In addition to saving time, drones are said to use resources efficiently, saving a significant amount of water. The cost-per-acre unit economics of drone spraying is beginning to catch up with that of manual labour and it reduces input costs by 18 %-20 % and increases crop yields by 30 %-100 % through precision farming. Drones also cut labour and operational costs while enabling efficient coverage of large areas quickly. Environmentally, they lower chemical usage by up to 50 %, conserve water by up to 90 % and reduce the carbon footprint by 25 %. Additionally, drones help reduce post-harvest losses by 50 % and support job creation, making them a key tool for sustainable and productive farming in India
Integrating traditional and emerging technologies for enhanced water quality monitoring and sustainable resource management
Full text linkGlobal water quality is increasingly threatened by industrial expansion, urbanization and climate change, necessitating robust and adaptive monitoring systems. This review critically examines the evolution of water quality assessment methodologies, transitioning from traditional field-based approaches to advanced technologies such as Artificial Intelligence (AI), constructed wetlands, remote sensing and Internet of Things (IoT)-enabled monitoring systems. Emphasis is placed on the evaluation of key water quality parameters, including physicochemical, bacteriological and heavy metal contaminants, across both surface and groundwater systems. Analytical tools such as the Water Quality Index (WQI), Geographic Information Systems (GIS), hydrus modelling, Multivariate Statistical Analysis (MSA) and regression-based machine learning models-including Artificial Neural Networks (ANN) and Hammerstein-Wiener (HW) models are reviewed in terms of their applicability and effectiveness. Bibliometric analysis is employed to uncover current research trends, interdisciplinary linkages and geographic hotspots in water quality research. The primary objective of this review is to synthesize current advancements, identify methodological gaps and propose an integrated framework that combines traditional techniques with modern analytics to enhance sustainable water resource management strategies
Accelerating AI-driven solutions for insect pest detection in Indian agriculture: A systematic review
Full text linkThe increasing demand for agricultural production is heavily constrained by biotic stresses such as insect pests, diseases and nematodes, which significantly reduce crop productivity. Traditional pest monitoring methods, which are often manual, time-consuming, labour-intensive and reliant on expert identification, are prone to human error and unsustainable for large-scale implementation. With the advent of digital agriculture, artificial intelligence (AI) has become a transformative tool for enhancing pest detection and management. AI-driven technologies, particularly those integrating computer vision, deep learning and machine learning, offer automated and accurate identification of pests, minimizing the misuse of chemical inputs and reducing ecological damage. Smart devices and sensor networks equipped with AI capabilities enable real-time surveillance of both biotic and abiotic stresses, promoting efficient, targeted and environmental conscious pest control strategies. This review systematically explores the historical development of AI based insect pest detection in India, highlighting their potential to enhance precision monitoring, reduce reliance on conventional practices and support sustainable crop protection. Furthermore, it addresses the key challenges associated with AI adoption in the identification of insect pests and outlines future research directions to accelerate the development and deployment of intelligent pest management systems
Unravelling genetic variability and character association study for cooking quality attributing traits for the selection of promising genotypes in rice
Full text linkRice (Oryza sativa L.) is a major cereal crop in the world, particularly in Asia, where it is a staple food for 90 % of the population. The current research was aimed at determining the better genotypes for cooking quality characteristics by utilizing forty-three genotypes of rice along with two checks, viz: Pooja and RNR 15048. The experiment was carried out during the summer season of 2024 at Post Graduate Research Farm, M.S. Swaminathan School of Agriculture, Centurion University of Technology and Management, Paralakhemundi, India. The design of experiment was Randomized Block Design (RBD) with three replications. Study revealed significant difference among all the studied parameters through analysis of variance which extend scope of further study. Genetic parameters revealed that phenotypic coefficient variation is higher than genotypic coefficient of variation indicates along with genotypic environment also played key role to influence the studied characters. High heritability coupled with high to moderate genetic advance as percent of mean noted for all the studied characters signify the predominance of additive gene action henceforth, direct selection would be rewarding. Character association and partial regression study revealed significant association among the studied variables. The significant character such as seed protein content highest exhibited by POO7SD (8 %), amylose content exhibited highest in Durgasal (24 %), on contrary lowest was revealed by Mugi (10 %). Genotypes RNR 15048, Pusa Basmati and POO7SD were found to be superior for biochemical and cooking quality traits and hold promise for future programs of improvement. Which clearly signify future potential to unravel qualitative breeding by seeing India’s opportunities in global market through Basmati rice. Therefore, further exploration of aforementioned genotypes will ultimately help to strengthen India’s qualitative rice market in domestic and international pace
Unveiling hard seededness and enhancing seedling vigor: Genotypic response and priming strategies in mung bean (Vigna radiata L.) under temperate conditions
Full text linkA comprehensive study was conducted at the Faculty of Agriculture, Wadura, SKUAST-Kashmir, to evaluate hard seededness and the effect of seed priming in mung bean (Vigna radiata L.) genotypes over two consecutive years (2021 and 2022). Genotypic variation for hard seededness was evident. In 2021, 80 of the total genotypes evaluated showed full germination, 36 had 1-5 hard seeds and 7 had more than 10 hard seeds, with hard seed counts ranging from 0 to 12. In 2022, only 52 genotypes achieved complete germination, while 60 genotypes had 1-10 hard seeds and 10 genotypes had more than 10, for a total range of 0 to 22 hard seeds. Notably, genotype PKV-AKM-4 consistently produced the highest number of hard seeds in both years (12 in 2021 and 22 in 2022). Furthermore, a seed priming experiment indicated substantial differences between mung bean genotypes and priming regimens. Rhizobium-treated seeds had the greatest average root depth (9.1 cm), root weight (0.099 g) and shoot weight (0.133 g). Trichoderma treatment produced the longest shoot length (7.3 cm), followed by Pseudomonas treatment, which produced a shoot length of 6.4 cm and a root weight of 0.064 g. These data show the effectiveness of microbial seed priming, particularly with Rhizobium and Trichoderma, in improving early seedling vigor in mung bean genotypes. The observed variance in hard seededness highlights the possibility for developing mung bean cultivars with lower dormancy to enable uniform field emergence. Microbial seed priming, notably with Rhizobium and Trichoderma, has been shown to significantly improve root and shoot development, as well as early seedling vigor. Adoption of these priming approaches can improve crop establishment and production stability under a variety of agroclimatic conditions
Impact of foliar application of organic formulations on plant growth, seed yield and quality in green gram (Vigna radiata L.)
Full text linkGreengram is one of the most important pulse crops in India. It plays a crucial role in organic farming systems due to its ability to fix atmospheric nitrogen. Productivity in organic farming is generally lower than in conventional systems, primarily due to the need for large quantities of organic amendments to meet crop nutrient requirements. Foliar fertilization serves as an efficient and cost-effective alternative for delivering essential nutrients directly to the plants. In this study, field experiments were conducted during the Kharif and Rabi seasons of 2024 using greengram (CO 9) seeds, following a Randomized Block Design (RBD) with nine treatments and three replications. Organic formulations including panchagavya, Fermented Fish Extract (FFE), Egg Fermented Extract (EFE) and Seaweed Extract (SWE) were sprayed at critical growth stages, specifically at flower initiation and early pod formation to evaluate their efficacy. The results indicated that two foliar applications of panchagavya 5 % (T2) recorded the highest plant growth and seed yield parameters. SWE 10 % (T4) recorded higher seed quality parameters followed by panchagavya 5 % (T2) which showed comparable performance. Hence, the foliar application of panchagavya 5 % at the flower initiation and early pod formation stages can significantly enhance plant growth, seed yield and quality, ultimately leading to improved productivity in greengram
Tracking nanonutrients in plants: A review of uptake, assimilation, translocation and analytical techniques
Full text linkThe development of nanotechnology in agriculture has fuelled the rise of nanonutrients as prospective agents to improve nutrient use efficiency, crop yield and environmental sustainability. In contrast to traditional fertilisers, nanonutrients offer targeted delivery, slow release and enhanced absorption due to their nanoscale size and distinctive physicochemical properties. This review critically assesses the existing knowledge on nano-nutrient uptake, assimilation and translocation in plant systems. It emphasises the intricate interactions between plant physiological pathways and nanomaterials, including entry modes through leaves and roots, transport mechanisms at the cellular level and their ultimate distribution within plant organs. Additionally, this article provides a detailed account of the methodological strategies employed to investigate these processes. These methods include elemental and isotopic tracing, spectroscopic and molecular analyses, imaging technologies, physiological and biochemical assays, as well as dye-based tracking systems. The combination of these methodologies has enhanced our ability to quantify, visualise and comprehend the fate of nanonutrients in planta. Synthesising recent breakthroughs and methodological updates, this review aims to establish a foundation for future studies that maximise nano-fertiliser design and ensure their safe and efficient deployment in sustainable agriculture