Horizon e-Publishing Group (HePG): E-Journals
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Amino acid-chelated micronutrients: A new frontier in crop nutrition and abiotic stress mitigation
No full textMicronutrient deficiencies and abiotic stresses, such as drought, salinity and temperature fluctuations, significantly reduce global crop productivity, partly by limiting nutrient bioavailability. While micronutrients are essential for plant metabolism, their precise application is crucial to prevent heavy metal contamination and environmental degradation. Overuse or improper application of micronutrients can lead to toxicity, soil degradation and groundwater contamination. To address these challenges, chelating agents have been introduced into agricultural systems to enhance micronutrient availability and uptake by plants. Amino acid chelates, a class of ‘smart fertilizers’ that bind micronutrients to amino acids, offer an innovative solution to enhance nutrient efficiency and mitigate abiotic stress effects. By enhancing nutrient absorption, promoting antioxidant activity, regulating osmotic balance and supporting enzymatic functions, amino chelates contribute to improved crop health and resilience. This review explores the current challenges in agriculture related to micronutrient deficiencies and abiotic stress, focusing on amino chelates as an advanced solution for improving nutrient uptake and crop resilience. However, there remain uncertainties regarding their synthesis and properties, optimal application rates and interactions with other agricultural inputs. The aim is to provide a comprehensive understanding of amino chelates, their mechanisms and future potential for sustainable agriculture, while emphasizing the need for targeted research to optimize their use in addressing micronutrient deficiencies and abiotic stress
GGE biplot analysis in rice landraces grown under rainfed ecosystem
No full textPlant breeders across the world frequently employ GGE Biplot analysis. Purpose of this study was to evaluate the GXE interaction and stable yield performance of 15 rice (Oryza sativa L.) landraces of southern India grown under rainfed ecosystem. All the rice landraces were sown in a randomized complete block design with three replications in five consecutive years in rabi season from 2018-19 to 2022-23 at Agricultural Research Station, Tamil Nadu Agricultural University, Paramakudi, Tamil Nadu. The pooled ANOVA over tested years / seasons revealed that both the genotypes and GEI (GXE interaction) significantly influenced grain yield and rice landraces performed contrarily in diverse testing years due to cross over nature of GEI. Biplots with the genotype main effect and GEI were used to study and display the trend of the interaction elements. About 95 % of the overall variation in the GGE model was explained by the first two principal components. (PC1 = 74.8 %, PC2 = 19.9 %). The “what-won-where” polygon was shown that G8 (Kallurundaikar), G11 (Kattanur), G4 (Sivapuchithiraikar) G5 (Kuruvaikalanjium) and G7 (Mattaikar) performed well in each environment and they were the highest-yielding among the landraces tested on the field. In terms of discriminating and representativeness for the environments, rabi 2019-20 was regarded as superior production season as per selectiveness for the testing sites. The rice landraces selected through this study may be utilized as parental lines in breeding for yield enhancement in rainfed situation of southern India or similar agro-ecological zones
Exploring the factors influencing the adoption of smart farming technologies in agriculture - A bibliometric analysis literature review
No full textSmart Farming Technologies (SFTs) play a crucial role in enhancing agricultural productivity, sustainability and resource efficiency. However, a variety of technological, economic, social and policy-related issues influence their adoption. This study uses bibliometric analysis to highlight collaborative efforts in this field, uncover global research trends and investigate the major factors impacting the adoption of SFT. The study uses Visualization of Similarities (VOS) viewer and R studio to perform bibliographic coupling, keyword co-occurrence and citation network analysis using Scopus as the main database. The selection of excellent, peer-reviewed studies is guaranteed via a PRISMA-based methodology. The results show notable differences in adoption rates, with affluent countries making tremendous progress while underdeveloped regions struggle with digital literacy, inadequate infrastructure and budgetary restraints. High upfront expenditures, problems with interoperability, worries about data privacy and farmers\u27 aversion to change are some of the main obstacles. Adoption rates are greatly impacted by social factors, institutional support and governmental regulations, underscoring the necessity of focused interventions. To close the gap between the development of technology and its practical application, the study emphasizes the value of collaborative research, interdisciplinary approaches and policy frameworks. To increase adoption, it is essential to address infrastructure and financial issues, improve farmer training and fortify policy measures. The findings deepen our understanding of the dynamics of smart farming adoption and provide evidence-based suggestions for industry executives, researchers and policymakers. To guarantee extensive SFT implementation and long-term agricultural resilience, future studies should concentrate on localized adoption models, sustainable financing and adaptable regulations
Recent developments in ready-to-use foods to improve the health status of moderate acute malnourished children
No full textDespite various government and nongovernment measures, malnutrition (low weight-for-height) remains a global concern among children and its prevalence is alarming. The contention that effective management of moderate acute malnutrition (MAM) prevents severe acute malnutrition (SAM) is supported by data demonstrating substantial reductions in the extent and prevalence of SAM in areas where MAM has been adequately treated. The reduction of childhood morbidity and mortality through an intervention is contingent on the study of foods used to treat children suffering from MAM. Therefore, a narrative review of the literature was conducted, providing a comprehensive background on recent developments in supplementary foods by summarising findings from a total of 17 studies that have the potential to manage MAM. The review also paves the way for possible future inventions. It was observed that the supplementary biscuits developed from local ingredients were more cost-effective and acceptable to children. The inclusion of fish in various forms of supplementary food could serve as a great source of valuable protein. Furthermore, ready-to-use, low-moisture peanut pastes were transformed using indigenous ingredients to make them more acceptable and the use of pre and probiotics in foods to manage malnutrition improved the gut microbiota of children. It was seen that the use of locally available ingredients to develop study foods could serve as an alternative for managing MAM
Phytochemical characterization by GC-MS and in vitro evaluation of antioxidant potential of Walsura piscidia Roxb. leaves extract
No full textWalsura piscidia Roxb. (Family: Meliaceae) is currently known for rich sources of bioactive compounds with growing multiple therapeutic and medicinal importance. The main objectives of this study were to characterize the phytochemical profile of the leaves of W. piscidia by Gas Chromatography-Mass Spectrometry (GC-MS), followed by the evaluation of its antioxidant potential by quantifying the amounts of phenols and flavonoids present within the extracts, through the existing methods of detection. The extractive yield calculated after Soxhlet extraction was seen to be higher for the ethanolic extract with a value of 21.9 %, followed by the methanolic extracts (21.06 %) and the qualitative phytochemical tests gave similar classes of phytochemicals like triterpenoids, phenolic compounds and tannins in the methanolic and ethanolic extracts. The total phenolic content was seen to be higher in the ethanolic extract with a value of 26.192 ± 0.401 mg GAE/g and the total flavonoid content was seen to be higher in the methanolic extract with a value of 42.972 ± 0.214 mg QE/g. The methanolic extract showed promising results in the antioxidant assays with a significantly low IC50 value in DPPH assay and high ferric reducing power in ferric reducing antioxidant power (FRAP) assay. The GC-MS chromatograms showed almost similar compounds for both the methanolic and ethanolic leaf extracts, some important ones being n-Hexadecanoic acid, stigmasterol, campesterol, 5-hydroxymethyl furfural, etc, displaying properties of interest like antioxidant, anti-inflammatory, anti-microbial, etc. This work contributes to our better understanding of the medicinal properties of the leaves of W. piscidia and has also provided a strong scientific basis to the traditional usage claims of this tree
Comprehensive analysis of nanotechnology-driven advancements and outlines future directions for sustainable biofuel production
No full textThe global energy crisis, environmental degradation and diminishing fossil fuel reserves have amplified the demand for sustainable energy alternatives. Biofuels derived from renewable resources offer a promising solution; however, their large-scale adoption is limited by challenges such as high production costs, scalability issues and low efficiency. This review examines the role of nanotechnology in overcoming these barriers by enhancing biofuel production processes. Nanostructured materials, renowned for their high surface area and catalytic efficiency are employed to optimize critical stages such as the pre-treatment of biomass, enzymatic hydrolysis and transesterification. This review emphasizes the utilization of advanced nanomaterials, including metal oxides, magnetic nanoparticles, carbon nanotubes and acid-functionalized nanoparticles, in improving production efficiency and enabling the use of non-edible feedstocks. These innovations not only boost economic viability but also reduce environmental remediation. Although these advantages exist, concerns related to nanoparticle toxicity, environmental safety and economic feasibility remain significant, necessitating future research. The review offers a comprehensive comparison of nanomaterial types, evaluates their performance in various stages of biofuel production and highlights their potential for industrial-scale application-providing fresh insights for future development. In this review, we provide a comprehensive analysis of nanotechnology-driven advancements and outlines future directions for sustainable biofuel production
Specific habitat preferences of Psilotum nudum (L.) P. Beauv on tree fern (Cyatheaceae): insight from Bali botanic gardens
No full textPsilotum nudum is an epiphytic fern belonging to the Family Psilotaceae. In Bali Botanic Garden, this plant grows on the stem of tree fern, but not all stands of tree fern become phorophytes for P. nudum. Studying P. nudum ecology in the Bali Botanic Garden is crucial in conservation efforts. The research was conducted in the Bali Botanic Garden area, using field observation methods on tree ferns located on the right and left of the main route of the garden. The data collected include tree fern species as hosts, the number of P. nudum individuals (clumps), P. nudum growing height and associated plants. The results showed that P. nudum was only found growing on one species of tree fern (phorophyte), Alsophila orientalis. Psilotum nudum is also associated with 43 species of plants. The most common plant species are Davalia denticulata (10.6%), Asplenium nidus (8.13%) and Dischidia sp. (6.91%). Host tree fern height has a weak but insignificant correlation with the number of P. nudum individuals (r = - 0.14, p = 0.5). The higher the Alsophila tree, the fewer P. nudum individuals were found. Host tree fern height was weakly correlated with the number of associated plant species (r= 0.24, p= 0.22). This data helps complete ecological data on collection plants that can be a reference in their development and cultivation efforts
Geographical indication of Kanyakumari Matti banana: A comprehensive analysis of farmer awareness, perception and constraints
No full textThe present study focuses on the awareness, perception and constraints of farmers about the GI tag of Kanyakumari Matti banana in Tamil Nadu state, India. Using data from 120 farmers across 3 blocks, socio-economic factors that impact GI awareness and perception are analysed through correlation and regression analyses. Constraints has been ranked by Garrett Ranking method. The result shows that the awareness is of a moderate nature, as 47.5% of farmers have medium awareness about GI. Out of 21 variables, 17 variables have been selected as per discussion with extension scientists. The variables like educational status, information-seeking behaviour and attitude towards GI were found to be significantly correlated with both awareness and perception. GI is perceived to be beneficial in protection of product origin and increased demand as per farmers (80.83%), whereas in the case of technological advancement, the percentage is 36.66% and unauthorized use prevention is 35%. Major constraints are lack of GI-specific training (71.86%) and market price fluctuation (98.26%). Targeted capacity building, infrastructure development and supportive policy are suggested for better adoption of GI and enhanced access to its market. These findings provide useful information for policymakers and stakeholders to design focused interventions that might enhance the economic benefit and sustainability of GI-certified agricultural produce
Modulating physiological constraints, abiotic stress and yield of sesame: Nutrients and plant growth regulators effects
No full textSesame (Sesamum indicum L.) is a crucial oilseed crop, yet it currently achieves only about 25% of its genetic yield potential. To harness the full potential of sesame, it is essential to develop well-defined phenotypes and crop architectures that exhibit a more effective source-sink relationship tailored to the specific cropping environment. Numerous physiological constraints hinder yield optimization, including indeterminate growth, poor source-sink relationships, flower drop, low seed retention and capsule and seed shattering. Notably, these constraints are interactions between nutrient and plant growth regulators, both significantly influence the growth and overall productivity of sesame. Sesame cultivation is currently limited by low yields due to a lack of production strategies. This study suggested improving sesame productivity through the application of nutrients and plant growth regulators. Future research programs need to develop the best research strategies for economic and sustainable development
Ginger price dynamics in the Eastern Himalayan Region: A case study of Meghalaya
Get PDFGinger contributes substantially to the agricultural sector in Meghalaya, yet comprehensive forecasting analyses that integrate both traditional and volatility-sensitive time series approaches to study its price movements are still scarce. In this study, we explore common time series yet very powerful forecast models, namely the autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and ARIMA with exogenous inputs (ARIMAX), along with autoregressive conditional heteroscedasticity (ARCH) and generalized autoregressive conditional heteroscedasticity (GARCH) models, to forecast the monthly price of ginger in Meghalaya. During the estimation process, attention was given to the intrinsic forecasting strengths and limitations of these models, as well as to essential time series diagnostics, including stationarity, parsimony and overfitting. The discussion in this study is based on the forecast results obtained from a real-time monthly price dataset spanning 10 years. While fitting the models to the dataset, special care was taken to select the most parsimonious model. To evaluate forecast accuracy and compare the performance of the different models applied to the time series of monthly ginger prices, we used seven forecast performance measures: ME (mean error), RMSE (root mean square error), MAE (mean absolute error), MAPE (mean absolute percentage error), MASE (mean absolute scaled error), AIC (Akaike information criterion) and BIC (Bayesian information criterion). The GARCH (1,1) model outperformed the others, yielding the lowest MAE (1,212.28), MASE (0.2817) and a high persistence in volatility (β₁ = 0.99772). The average price during the study period was ₹4400.47. The forecasts indicated a decline in prices from ₹11910 in March 2024 to ₹10938 in July 2024