Fast-food consumption is embedded in contemporary childhood and adolescent food environments, yet the strength of evidence linking this exposure to health and developmental outcomes varies markedly by outcome and study design. This critical narrative review integrates evidence on dietary quality, adiposity, cardiometabolic risk, academic and psychosocial outcomes, environmental determinants, and policy responses. Literature published from 1 January 2000 to 30 June 2026 was identified through live searches of major open scholarly sources, supplemented by citation searching and verification of bibliographic metadata and digital object identifiers. The evidence is most consistent for immediate dietary consequences: on days when children or adolescents consume fast food, total energy intake and intakes of sugar-sweetened beverages, total and saturated fat, sodium, and added sugars tend to rise, while fruit, vegetables, milk and fibre-rich foods are displaced. Associations with adiposity are directionally plausible and supported by several longitudinal studies, but effect sizes are less consistent than for diet quality, and systematic reviews show substantial heterogeneity arising from exposure definition, residual confounding, reverse causation, and imperfect measurement of neighbourhood food access. Direct paediatric evidence for metabolic syndrome is limited but includes a prospective cohort signal. Reported associations with academic achievement, sleep disturbance and psychological distress are potentially important but remain predominantly observational; broader “junk food” or ultra-processed food evidence should not be treated as equivalent to fast-food-specific evidence. Marketing exposure, parental consumption, affordability, neighbourhood retail structure, and adolescent autonomy appear to shape consumption, often in socially patterned ways. Policy evidence indicates that information-only approaches such as calorie labelling have modest effects, whereas healthier defaults, marketing controls, price strategies and reformulation may be more promising when implementation and compliance are strong. Future research requires repeated objective exposure measurement, longer follow-up, stronger quasi-experimental designs, greater representation of low- and middle-income countries, and explicit separation of fast-food source, processing level and overall dietary pattern. Overall, frequent fast-food consumption is best regarded as a modifiable marker and contributor to poorer dietary quality, with probable but less precisely quantified downstream effects on weight and metabolic health and still-uncertain independent effects on broader development.
In this era of rapid population growth, the world is changing rapidly, increasing the need for timely dissemination of information and knowledge. Therefore, the present study was conducted to assess farmers' needs so that, based on those needs, different approaches can be undertaken to improve their livelihoods. The study was conducted in Nagaon district of Assam and covered 200 sample farmers. A combined questionnaire and interview approach was used together with Participatory Rural Appraisal and Rapid Rural Appraisal methods. The findings showed that farmers need seeds and fertilisers at the right time to make the KVK system more effective. Irrigation was the second-ranked need, while an improved market network, farm mechanisation, and greater emphasis on horticulture ranked third, fourth, and fifth, respectively. Similarly, among production problems, animal menace was the major problem faced by farmers, followed by pests and diseases; among marketing problems, storage facilities were the main problem, followed by processing and assembling. Hence, farmers' opinions and experiences should be given importance while formulating agricultural policies and development programmes. More scientific and modern technologies should be developed and made accessible to farmers to address problems such as animal menace, insect pests, and crop diseases. In addition, proper storage and preservation facilities need to be improved, as most agricultural products are perishable in nature. Better storage infrastructure, cold chains, and processing facilities can help reduce post-harvest losses and increase farmers' income.
Ornamental sunflower has gained popularity as a cut flower owing to its attractive appearance, short growth cycle, and market demand, although limited information is available regarding its economic feasibility and commercial potential under Indian conditions. Therefore, the present study was undertaken to evaluate the economic performance and profitability of ornamental sunflower cultivation. The experiment was laid out in a Factorial Completely Randomized Design with three replications and was conducted at the Department of Floriculture and Landscaping, College of Horticulture and Research Station, Mahatma Gandhi University of Horticulture and Forestry, Durg, Chhattisgarh, India, during the summer seasons of 2024–25 and 2025–26. It comprised two factors: four humic acid concentrations (no humic acid application; humic acid at 10 mL/L water; humic acid at 20 mL/L water; and humic acid at 30 mL/L water) and three organic leachates (no leachate application, vermicompost leachate, and neem cake leachate). These treatment combinations were used to calculate the economics of ornamental sunflower cultivation. Among the treatments studied, the highest B:C ratio (3.31) was obtained with T8 (humic acid 20 mL/L + vermicompost leachate), followed by T9 (humic acid 20 mL/L + neem cake leachate) with a B:C ratio of 3.30. The minimum B:C ratio (2.05) was recorded for the control treatment, T1. These results indicate the economic potential of T8 for commercial cultivation and for improving growers’ income.
A decade-long field investigation was carried out at the one-hectare Integrated Farming System (IFS) research model of the AICRP-IFS, Farming System Research Centre, SKUAST-Jammu, Chatha, and at an adjoining farmer’s field representing the existing farming system (EFFS), to characterise the depth-wise (0–15, 15–30, 30–45 and 45–60 cm) distribution of soil organic carbon (SOC), microbial biomass carbon (MBC), total organic carbon (TOC), oxidizable organic carbon fractions, active and passive carbon pools, and carbon management indices under twelve land use systems of the IFS model vis-à-vis EFFS. SOC, MBC and TOC were all significantly higher under boundary plantation intercropped with turmeric (up to 10.15 g kg⁻¹, 175.34 µg g⁻¹ and 28.00 g kg⁻¹, respectively, at the surface) than under the other land uses, and consistently lowest under EFFS (5.33 g kg⁻¹, 84.78 µg g⁻¹ and 16.80 g kg⁻¹). Among the oxidizable carbon fractions, non-labile carbon (Cₙₗ) formed the largest share of total organic carbon in all land uses, followed by very labile (Cᵥₗ), labile (Cₗ) and less labile carbon (Cₗₗ), with boundary plantation recording the highest values of every fraction at every depth. The active carbon pool (Cₐₚ = Cᵥₗ + Cₗ) and passive carbon pool (Cₚₚ = Cₗₗ + Cₙₗ) followed the same land-use ranking, with Cₚₚ exceeding Cₐₚ at every depth in every land use. The sensitivity index at the surface depth was highest for microbial biomass carbon under boundary plantation (106.82%) and lowest for the non-labile carbon fraction across land uses, while the lability index, carbon pool index and carbon management index (CMI) were all highest under boundary plantation at every depth (CMI = 142.56 at 0–15 cm, declining to 51.95 at 45–60 cm) and lowest under EFFS (CMI = 74.82 at 0–15 cm, the reference value). Most carbon fractions and pools decreased with increasing soil depth, while CMI declined consistently across all land uses. These results indicate that a decade-long integration of tree-based (boundary plantation) and fodder components under IFS, supported by vermicompost recycling, builds up both the quantity and the lability-weighted quality of soil organic carbon more effectively than continuous mono-cropping, with clear implications for soil carbon sequestration planning in the North-Western Himalayas.
Hospitals occupy an unusual position within the built environment. They operate continuously, maintain tightly regulated indoor conditions for clinical reasons, house diagnostic and therapeutic equipment with sharp and irregular power draws, and carry an obligation of uninterrupted supply that few other building types share. These characteristics have made hospital energy systems an attractive target for predictive analytics and machine learning, and a distinct body of applied work has accumulated over the past decade. That literature nonetheless remains difficult to interpret. Reported accuracy rankings among algorithm families are mutually inconsistent, most studies are built on a single facility, validation protocols vary widely, predictive uncertainty is rarely quantified, and the operational consequences of improved forecasts are seldom measured. This critical narrative review examines the state of knowledge on data-driven forecasting of hospital energy demand and on the use of such forecasts for load optimisation. Literature was identified through structured searching of open scholarly indexes, supplemented by backward and forward citation searching, with a final search date of 22 June 2026. The synthesis is organised around four analytical problems: the structural features that make hospital demand different from other non-residential demand; the contested evidence on model superiority; the methodological weaknesses that limit confidence in reported performance; and the weak evidentiary chain linking forecast accuracy to operational or economic benefit. The available evidence supports several defensible conclusions. Activity-related predictors improve accuracy beyond weather and calendar variables; ensemble and hybrid methods perform robustly at daily resolution; and deep architectures show advantages mainly at sub-hourly resolution when training records are long. Confidence in claimed hierarchies among model families remains limited, and evidence that forecasting systems reduce hospital energy cost, emissions or peak demand under clinical constraints is preliminary. Research priorities include multi-site benchmarking, decision-linked evaluation, probabilistic forecasting, and reporting standards adapted to critical-care settings.
Agriculture is being revolutionized through the integration of cutting-edge technologies that support efficiency, productivity, and sustainability. Recent trends in transforming traditional agriculture into smart agricultural systems through the application of Artificial Intelligence (AI), IoT, and drone technology are gaining popularity worldwide. In this context, the current study developed an integrated artificial intelligence-based farming system incorporating Internet of Things sensors, drones, deep learning, and web/mobile applications for timely monitoring of crop and aquatic health. Data were collected using IoT sensors and drones equipped with high-resolution cameras to monitor soil and water parameters, including temperature, humidity, and pH, under various climatic conditions. A dataset of 70,000 images was used for system training, validation, and testing with an 80:10:10 split, together with three months of IoT sensor data. Models including YOLOv8, CNN, Faster R-CNN, ResNet50, MobileNet, EfficientNet, DenseNet, LSTM, and Random Forest were used for pest and disease detection, fish classification, fish disease detection, shrimp disease detection, and monitoring of climatic factors. Data pre-processing included denoising, normalization, missing-value handling, and feature extraction. The designed model showed reliable performance across the tasks, with 88.4% accuracy for shrimp detection, 92.1% for pest detection using YOLOv8, and 93.4% accuracy for plant disease detection using the CNN model. Overall performance was recorded at 97% accuracy, with high precision, F1-score, and mAP, and an RMSE of 1.2 for sensor-based prediction and validation. The current findings indicate the potential of using AI, IoT, and drone technologies to detect biotic and abiotic stresses during farming and support a sustainable agricultural system.
Soymeal is an important protein-rich by-product of soybean processing and a significant component of India’s agricultural exports. This study analysed the direction of trade and changing export pattern of Indian soymeal from 2014–15 to 2023–24. Secondary export data were obtained from the Directorate General of Commercial Intelligence and Statistics (DGCI&S), Kolkata, for soymeal under HS Code 23040030. A first-order Markov chain approach, with transition probabilities estimated using the Minimum Absolute Deviations method, was applied to assess the stability and redistribution of export shares among major importing markets. The analysis covered Japan, South Korea, Indonesia, Myanmar, Sri Lanka, Thailand, Vietnam and Bangladesh, with all remaining destinations grouped as Other Countries. The results showed substantial instability across the traditional markets. Japan, South Korea, Indonesia, Thailand, Vietnam and Bangladesh recorded zero retention of their previous export shares, while Myanmar and Sri Lanka retained 5.3 per cent and 25.5 per cent, respectively. In contrast, Other Countries showed the highest market retention probability at 81.5 per cent and absorbed sizeable shares lost by several traditional destinations. Overall, the findings indicate a shift in India’s soymeal exports from individual traditional markets towards a more diversified group of destinations. Strengthening competitiveness in established markets while sustaining access to emerging destinations may support greater stability in India’s soymeal export trade.
A six-week feeding trial was carried out to examine how dietary coriander seed, turmeric powder and black pepper influence feed intake, growth, feed efficiency, blood parameters, carcass traits, meat acceptability and the economics of broiler production. Two hundred and forty day-old chicks were randomly allocated to four dietary treatments, with three replicates of 20 birds each: unsupplemented control (T1), coriander seed at 2% (T2), turmeric powder at 2% (T3) and black pepper at 0.5% (T4). Feed intake and body weight were recorded weekly, while feed conversion ratio was calculated from cumulative feed intake and body weight gain. At the end of the trial, blood indices, carcass traits, organ weights and sensory attributes were assessed. Birds receiving the supplements consumed more feed overall than the control birds. The highest cumulative intake was recorded in the turmeric group (T3; 3422.00 ± 22.10 g/bird), followed by coriander (T2; 3367.90 ± 21.90 g), black pepper (T4; 3333.90 ± 21.80 g) and the control (T1; 3140.10 ± 22.95 g). Supplemented birds also finished the trial at higher body weights. The coriander group recorded the highest final body weight (1964.40 ± 31.61 g), compared with 1790.83 ± 23.64 g in the control, while black pepper and turmeric groups reached 1940.80 ± 31.30 and 1915.25 ± 34.26 g, respectively. Overall FCR did not differ significantly among treatments, although numerically lower values were observed in T2 and T4. Haemoglobin, PCV, TEC, TLC and ALT were not significantly affected, whereas AST was higher in all supplemented groups than in the control. Live weight, dressed weight, dressing percentage, visceral organ weights and sensory attributes were not significantly altered. The highest return over feed cost (Rs. 1825.60 per 60-bird batch) and profit per chick (Rs. 31.47) were obtained with coriander seed supplementation. Taken together, the results suggest that adding coriander seed at 2% offered the most favourable balance between growth performance and economic return under the conditions of this experiment. The supplementation did not produce detectable adverse effects on the carcass and haematological traits measured in the study.
Cattle dung collection in many small and medium-sized dairy farms is still performed manually using conventional tools, making the operation labour-intensive, time-consuming, and unhygienic. The present study aimed to design, develop, and evaluate a battery-operated cattle dung collector to reduce labour requirements and promote mechanisation in animal husbandry. A survey of five dairy farm owners in Raipur district, Chhattisgarh, was conducted to assess existing dung collection practices and the economics of dairy farming. The engineering properties of fresh cattle dung, including moisture content, total solids, bulk density, coefficient of static friction, and dynamic viscosity, were determined and considered in the design of the machine. The developed machine consisted of a mild steel frame, plate-type collection unit, and chain-and-sprocket transmission system, powered by a 0.5 hp (373 W) DC motor and a 25.6 V LiFePO₄ battery. Machine performance was evaluated on smooth and rough floor surfaces at operating speeds of 0.5, 1.0, and 1.5 km h⁻¹ using a factorial randomised block design. Manual dung collection required multiple labourers, whereas the developed machine required only one operator, thereby reducing the labour requirement for dung collection. The maximum collection capacity of 342.81 kg h⁻¹ and collection efficiency of 89.05% were obtained at 1.0 km h⁻¹ on a smooth floor. The minimum quantity of cattle dung left after collection was 0.440 kg under the same operating conditions. The fabrication and operational costs of the machine were ₹60,000 and ₹59.54 h⁻¹, respectively, including labour costs. The break-even point was 398.37 h year⁻¹, and the payback period was 4.03 years. Under the tested conditions, an operating speed of 1.0 km h⁻¹ on a smooth floor provided the most favourable performance. The developed machine reduced labour requirements and demonstrated potential for improving the efficiency and mechanisation of cattle dung collection in dairy farms.
Fruits are an important component of the daily diet. India is the second-largest producer of both fruits and vegetables globally, after China. The economic impacts of the COVID-19 pandemic have been widely studied in many countries. The pandemic also substantially affected postharvest supply chains, transportation, retail marketing, and the trade of fruits and vegetables. However, the impact of the COVID-19 pandemic on horticulture, particularly the fruit sector, has been less studied in India. Therefore, this study was conducted to analyse the impact of the COVID-19 pandemic on prices and changes in consumer behaviour during the pre-COVID (2019-20) and COVID (2020-21) periods. Price analysis was conducted using data obtained from the National Horticulture Board, Government of India. For the consumer behaviour analysis, a prepared questionnaire was administered to a diverse group of people (students, employees, and friends) living in Bangalore city. The study revealed that higher load arrivals in the market had a negative influence on wholesale prices, resulting in lower prices. In contrast, the consumer survey showed that fruit prices were perceived to be higher during COVID than during the pre-COVID period. The survey also revealed that COVID-19 significantly influenced consumer behaviour in terms of perceptions of fruit prices, frequency of fruit purchases, preferences for different fruits, purchases of new and exotic fruits, and awareness of the nutritional aspects of fruits. Understanding the influence of the COVID-19 pandemic on transportation, prices, availability, and consumer attitudes may support crucial policy decisions and welfare measures for the pomology sector and society.
Climate change and global warming have profound impacts on various sectors of human society, with agriculture being among the most vulnerable. Rising temperatures, altered precipitation patterns, and an increased frequency of extreme weather events adversely affect agricultural productivity by reducing the yields of many crops and creating favourable conditions for the proliferation of weeds, pests, and diseases. The present study was conducted in Jhunjhunu district of Rajasthan, with Mandawa tehsil purposively selected because it had the highest number of farmers registered under the NICRA project. Three villages, namely Bharoo, Chakwas, and Madansar, were subsequently selected for the study. A proportionate random sampling technique was used to select registered farmers as NICRA beneficiaries, while an equal number of non-beneficiary farmers were randomly selected from the same villages for comparison. The findings revealed that the adoption of climate-resilient technologies under the NICRA project led to notable improvements among beneficiary farmers, including increases in irrigated area (8.92%), crop yield (51.71%), cropping intensity (23.35%), and annual income (84.29%). Furthermore, the majority of beneficiaries (76.67%) experienced a medium level of impact from the project, followed by 15.00% who reported a high level of impact and 8.33% who experienced a low level of impact.
Aims: To retrospectively assess the occurrence, clinical presentation, diagnostic patterns, and therapeutic management of dermatological conditions in dogs presented to a university teaching veterinary hospital in Punjab, India, and to determine their association with season, age, breed, and coat characteristics. Study Design: Retrospective observational study. Place and Duration of Study: University Teaching Veterinary Hospital, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab, India, from January 2018 to December 2020. Methodology: During the three-year study period, clinical records of dogs presented for evaluation were retrospectively reviewed. Dogs diagnosed with dermatological conditions were identified, and data pertaining to the type of dermatological disorder, clinical signs and primary owner complaints, season of presentation, age, breed, body size, hair-coat characteristics, and therapeutic interventions were analysed. Statistical associations between dermatological conditions and demographic and seasonal variables were assessed, and relative risks for commonly encountered dermatological conditions were determined. Results: During the study period, dermatological conditions accounted for 6.2% of all dogs examined, with a total of 2,853 cases recorded. The most frequently diagnosed conditions, in descending order, were tick infestation (26.2%), dermatitis (21.0%), superficial pyoderma (14.0%), demodicosis (8.0%), otitis externa (7.9%), allergy (7.4%), and pododermatitis (6.1%). The predominant clinical signs and owner-reported complaints were pruritus (95.5%), erythema (73.0%), and alopecia (52.5%). The occurrence of dermatological conditions was significantly associated with season, age, sex, and breed characteristics, with the highest occurrence observed during the monsoon–autumn season (47.5%), in dogs aged >1–5 years (56.8%), small- (40.2%) to medium-sized breeds (46.6%), and short-haired breeds (74.5%). Increased relative risks for selected common dermatological conditions were also observed in relation to season, age, and breed characteristics. Management predominantly involved combinations of systemic and topical medications, including antihistamines, antibiotics, antiseptics, ectoparasiticides, and skin-health formulations. Conclusion: Canine dermatological disorders constitute a substantial portion of clinical presentations in dogs, with ectoparasitic, inflammatory, infectious, and allergic conditions being the most prevalent. The incidence of these disorders is significantly influenced by season, age, breed, body size, and coat characteristics. The findings underscore the significance of considering these epidemiological risk factors for early recognition, targeted diagnosis, prevention, and rational therapeutic management of canine dermatological diseases in veterinary practice.
Background: Simulated microgravity (SMG) can perturb endothelial redox regulation, but the temporal development of these responses during early exposure remains insufficiently characterised. Aim: To elucidate whether simulated microgravity-induced redox modulation in endothelial cells initiates adaptive responses towards redox homeostasis. Study Design: The 3D clinostat provides a useful and cost-effective platform for generating SMG. EA.hy926 cells were exposed to SMG for 6, 12, and 24 h, while static control (SC) cells were maintained under normal gravity (1 × g). Place and Duration of Study: The study was conducted in the Department of Biotechnology, The University of Burdwan, West Bengal, India, between August 2022 and January 2024. Methodology: The human endothelial cell line EA.hy926 was used as the experimental model. Simulated microgravity was generated using a three-dimensional (3D) clinostat. Following treatment, cell viability, intracellular reactive oxygen species (ROS), catalase activity, superoxide dismutase (SOD) activity, lipid peroxidation, and the GSH/GSSG ratio were evaluated using standard biochemical assays. Data were analysed using one-way analysis of variance (ANOVA) followed by an appropriate post hoc test and expressed as the mean ± SEM (P < 0.05). Results: Cell viability remained unaffected following SMG exposure for 6, 12, and 24 h. Intracellular ROS generation increased significantly after 6 h and declined progressively at 12 h and 24 h, although it remained elevated compared with the corresponding static controls. Catalase and SOD activities were significantly reduced at 6 h and gradually increased with increasing exposure duration. Lipid peroxidation was markedly elevated at 6 h and progressively decreased at 12 h and 24 h. The GSH/GSSG ratio was significantly reduced after 6 h and gradually increased at 12 h and 24 h. Conclusion: SMG induced an early oxidative stress response without compromising cell viability, followed by the initiation of antioxidant-mediated restoration of redox balance. Although longer exposure durations are required to confirm complete redox homeostasis, these findings improve our understanding of the early endothelial response to SMG and its potential implications for managing vascular dysfunction during prolonged microgravity exposure.
Aim: The present investigation was conducted at the Agricultural Research Farm, Department of Horticulture, School of Agriculture, Suresh Gyan Vihar University, Jaipur, Rajasthan, during 2025–26 to study the effects of planting dates and spacing on the production of chilli (Capsicum annuum L.). Place and Duration of Study: The experiment was conducted during the Rabi season of 2025–26. Methodology: The experiment was laid out in a factorial randomised block design (FRBD) with two factors and three replications. The first factor comprised planting dates (three levels, viz. 30th June, 15th July, and 30th July), and the second factor comprised spacing (three levels, viz. 45 × 30 cm, 45 × 45 cm, and 60 × 45 cm). Results: The results revealed significant differences among the treatments. Among the growth parameters, the maximum plant heights at both stages, 52.00 cm at 45 DAT and 82.00 cm at 60 DAT, were observed in D2 × S3. The maximum numbers of branches per plant (30.03) and leaves per plant (125.10) were observed in D1 × S3, whereas the maximum plant spread (82.03 cm) was recorded in D2 × S3. Among the yield parameters, the maximum number of fruits per plant (79.57), fruit diameter (2.50 cm), average fruit weight (5.90 g), and fruit yield per plant (469.35 g) were observed in D2 × S3 (15 July × 60 × 45 cm). The maximum fruit length (12.33 cm) was observed in D1 × S3, whereas the maximum fruit yield per plot (18.02 kg) and total yield (16.68 t/ha) were recorded in D2 × S1. Among the quality parameters, the maximum TSS (6.9 °Brix) was recorded in D2 × S3, whereas the maximum capsaicin content (61.99 mg/100 g) and vitamin C content (195.50 mg/100 g) were recorded in D1 × S3 (30 June × 60 × 45 cm). The maximum net return (Rs. 343,792.67) and B:C ratio (3.81) were recorded in D2 × S1. Conclusion: The present investigation indicated that D2 × S1, representing chilli planted on 15 July at a spacing of 45 × 30 cm, produced the most favourable yield and economic returns. Therefore, this treatment combination may be recommended for chilli cultivation in this region.
Opportunistic mobile-phone recordings constitute a substantial component of civilian material submitted for unidentified anomalous phenomena (UAP) research, yet their scientific value is constrained by uncertain provenance, computational imaging, compression and lack of calibration. This study examined whether a previously published three-phase imaging workflow could be transferred to an independent, ambiguous luminous aerial recording from the Pilbara region of Western Australia. A screening-first case-study design documented event context and chain of custody, assessed astronomical, aviation, mine-site, orbital, atmospheric and instrumental candidates, and examined a contiguous 50-frame sequence, with 15 representative frames illustrating the range of recorded appearances. The adapted workflow used classical RGB and contrast enhancement, centroid-based exploded-frame deconstruction and two-dimensional Fourier-domain coherence processing. Findings were interpreted according to image domain: sequence-level recurrence for Phase 1, source-crop traceability for Phase 2 and whole-scene interpretation for Phase 3. Screening produced no positive identification, although incomplete timing, camera calibration and archival records prevented categorical exclusion. Phase 1 documented target persistence, relative colour-intensity change and peripheral asymmetry. Combined enhancement and exploded-frame processing exposed nonuniform intensity regions within an isolated Target A crop but could not distinguish a definitive source structure from camera or processing effects. Exploratory whole-scene coherence processing produced concentrated responses at locations corresponding to Targets A and B but did not establish target-specific structural replication. Replication was strongest for sequence-level colour-intensity variation and peripheral asymmetry. However, internal architecture, target-centred coherence, trajectory and wake behaviour were not securely reproduced. The workflow is best suited to conservative intake, triage and comparative assessment of citizen-derived UAP imagery rather than for determining object identity, mechanism or origin.
Introduction: Climate change has emerged as one of the most significant challenges to agricultural sustainability and natural resource management, particularly in arid and semi-arid regions such as Rajasthan. Study Period: This study examined the spatial and temporal variability of maximum temperatures across the 33 districts of Rajasthan using 23 years of secondary meteorological data for 2001–2023. Methodology: Descriptive statistical measures (mean, standard deviation, skewness and kurtosis) and parametric cubic trend models were employed to analyse temperature behaviour. The cubic model was fitted based on the coefficient of determination (R²), and model significance was tested using the F-value. Findings: The results revealed substantial spatial variation in maximum temperature among the districts. The mean maximum temperature ranged from 35.53°C in Rajsamand to 47.08°C in Hanumangarh, with relatively high values observed in Ajmer (44.91°C), Ganganagar (38.73°C), Jhalawar (38.64°C), Jalore (38.42°C) and Jodhpur (38.29°C). Hanumangarh recorded the highest observed maximum temperature (48.69°C), whereas Ajmer showed the greatest variability (SD = 1.313), indicating pronounced fluctuations during the study period. In contrast, Jhalawar exhibited the lowest variability (SD = 0.464). The cubic model consistently provided the best representation of maximum-temperature trends, with the highest explanatory power observed in Udaipur (R² = 0.473), followed by Rajsamand (0.456), Dungarpur (0.444), Pratapgarh (0.441) and Tonk (0.434). Several districts, including Udaipur, Rajsamand, Bharatpur, Banswara and Sirohi, exhibited statistically significant model fits (p < 0.05), indicating pronounced nonlinear temperature dynamics. Conclusion: The study highlights considerable inter-district climatic heterogeneity and emphasises the need for district-specific climate-adaptation strategies, heat-stress management, efficient irrigation planning and climate-resilient agricultural policies to enhance the sustainability of Rajasthan's agricultural systems.
Ginger (Zingiber officinale Roscoe) occupies a commercially and nutritionally important position within India's diverse spice sector. As the world's largest producer, India contributes substantially to the global ginger supply; however, its export orientation has historically remained modest relative to domestic production. This study empirically examines growth trends, instability, export performance, and price dynamics in India's ginger sector over the 20-year period from 2005–06 to 2024–25, divided into Phase I (2005–06 to 2014–15) and Phase II (2015–16 to 2024–25). The analytical tools include the compound growth rate (CGR), estimated using a log-linear exponential model, and the Cuddy–Della Valle Index (CDVI) for measuring instability. Ginger production recorded a CGR of 11.41 per cent over the full study period, supported by yield growth of 7.81 per cent and area growth of 3.33 per cent. The reported CDVI values indicate greater instability in production (19.50) and yield (15.07) than in area (8.99). Export performance improved considerably, with volumes rising sharply in 2020–21 and 2021–22; however, the concentration of exports in Bangladesh represents a structural vulnerability. Wholesale prices from November 2022 to December 2025 followed a pronounced cyclical pattern, increasing to more than ₹12,000 per quintal in 2023, declining sharply thereafter, and partially stabilising at approximately ₹6,000–₹7,000 per quintal in late 2025. The findings support measures to improve production stability, diversify export markets, strengthen post-harvest systems, and expand value addition to enhance India’s competitiveness in the global ginger trade.
Climate change continues to threaten agricultural productivity, food security, and nutritional outcomes among smallholder farming households in sub-Saharan Africa, necessitating the adoption of climate-smart and nutrient-dense crop varieties. Biofortified bean varieties, particularly the Nyota variety, have emerged as an important intervention for addressing micronutrient deficiencies while enhancing resilience to climate variability through improved productivity and drought tolerance. Despite their potential, adoption rates remain uneven due to a combination of socioeconomic, institutional, technological, and farm-level factors. This study investigated the determinants influencing the adoption and utilisation of the Nyota biofortified bean variety among smallholder farmers in Elgeyo Marakwet County, Kenya. A cross-sectional survey design was employed involving 210 smallholder farmers selected using probability sampling techniques. Primary data were collected through structured questionnaires and analysed using descriptive statistics, Chi-square tests, Pearson correlation analysis, and binary logistic regression to determine the factors influencing adoption. The findings revealed that 63.8% of the respondents had adopted the Nyota biofortified bean variety, indicating a relatively high level of acceptance within the study area. Socioeconomic characteristics significantly associated with adoption included gender (χ² = 5.42, p = 0.020), education level (χ² = 18.63, p < 0.001), household income (χ² = 14.27, p = 0.001), and age (χ² = 8.71, p = 0.013). Institutional factors also played a significant role, with access to extension services (χ² = 29.82, p < 0.001), agricultural training (χ² = 17.74, p < 0.001), farmer group membership (χ² = 15.31, p < 0.001), and access to agricultural credit (χ² = 8.93, p = 0.003) positively influencing adoption decisions. Technological attributes strongly shaped farmers' preferences, with drought tolerance (85.2%), high yield potential (81.4%), early maturity (80.0%), and improved grain quality identified as the most desirable characteristics. Among these, drought tolerance emerged as the strongest predictor of adoption (OR = 3.19), underscoring the importance of climate-resilient traits in farmers' varietal choices. The study further established that the majority of respondents were smallholder farmers cultivating relatively small land holdings under rain-fed production systems, making them particularly vulnerable to climate variability and production risks. The binary logistic regression model was statistically significant (Model χ² = 98.64, p < 0.001), explained 56% of the variation in adoption (Nagelkerke R² = 0.56), demonstrated good model fit (Hosmer–Lemeshow test, p = 0.61), and achieved an overall prediction accuracy of 82.4%. The study concludes that improving access to extension services, strengthening farmer training programmes, expanding agricultural credit facilities, promoting farmer organisations, and enhancing the dissemination of climate-resilient biofortified bean technologies would substantially increase adoption and utilisation of the Nyota variety. Scaling up these interventions has significant potential to improve household food and nutrition security, increase farm productivity and incomes, strengthen resilience to climate change, and contribute to sustainable agricultural development among smallholder farming communities in Kenya.
The study assessed and compared the livelihood support systems of small and marginal farmers and agricultural labourers in the Northern Dry Zone and the Southern Transition Zone of Karnataka. Primary data were collected from 240 respondents, comprising 160 small and marginal farmers and 80 agricultural labourers, through personal interviews using a well-structured interview schedule. A multistage purposive random sampling technique was employed to select respondents across four taluks in each agro-climatic zone. A Composite Livelihood Security Index (CLSI) was constructed using six dimensions, namely economic security, food security, education security, health security, habitat security and social security, following the Iyengar and Sudarshan indicator-weighting approach. Principal Component Analysis (PCA) was used to validate the dimensional structure of livelihood security, while a Fractional Probit model was employed to identify the determinants of livelihood security separately for farmers and agricultural labourers. The results revealed that the Composite Livelihood Security Index was higher in the Southern Transition Zone (0.532) than in the Northern Dry Zone (0.425). More than half of the households in the Southern Transition Zone (50.80%) belonged to the high livelihood security category, compared with only 2.50 per cent in the Northern Dry Zone. The Southern advantage was proportionally larger for farmers (28.0%) than for agricultural labourers (18.5%). Fractional Probit estimates indicated that Southern-zone location was positively associated with livelihood security among farmers (β = 0.245; p = 0.061). Among agricultural labourers, institutional participation had the largest positive coefficient (β = 0.157), although the estimate was not statistically significant. The findings highlight regional disparities in livelihood security and emphasise the need to strengthen livelihood support systems for vulnerable rural households across different agro-climatic zones of Karnataka.
Agriculture and allied sectors support rural livelihoods in India, and floriculture has emerged as a high-value component of horticulture. Roses are particularly important because of their cultural, ornamental, and commercial uses. This study analyses the rose value chain in Karnataka. Primary data were collected through a multistage purposive sampling procedure from 80 rose growers in Bengaluru Rural and Chikkaballapura districts, together with wholesalers, retailers, and processors. Secondary government data were used to examine trends in area, production, and yield. The analytical tools included the compound annual growth rate, the Cuddy Della Valle Instability Index, marketing efficiency indices, and the producer’s share in the consumer’s rupee. Karnataka recorded the highest rose yield and a substantial share of national production, although production and yield showed considerable variability. Processing roses into rose water and gulkand increased product value, with gulkand recording value addition of 57.03 per cent. The marketing analysis showed producer shares of 95–96 per cent and marketing efficiency indices of 19.58 for rose water and 24.79 for gulkand. The findings indicate that value addition and structured marketing channels can enhance returns within the rose value chain. Smart agriculture tools, including IoT-based monitoring, data-driven decision-making, and e-marketing platforms, may further improve coordination, reduce post-harvest losses, and support more efficient and sustainable floriculture systems in Karnataka.
