Prevalence of non-motor symptoms in Parkinson’s disease

Background: Parkinson’s disease is a common neurodegenerative movement disorder characterised by motor symptoms of rest tremor, bradykinesia, rigidity and postural instability and non-motor symptoms (NMS) which include neuropsychiatric symptoms, sleep disturbances, autonomic symptoms, sensory symptoms and symptoms of mixed aetiology. Parkinson’s Disease Non Motor Group (PD-NMG) devised a comprehensive clinic-based self-completed NMS questionnaire that allows easy identification of NMS by the physician. Most NMS have a poor response to dopaminergic therapy as it is due to dysfunction of the serotonergic and noradrenergic pathways. Treatment of these nonmotor symptoms help in improving the quality of life in patients with Parkinson’s disease.Methods: There were 100 patients with Parkinson’s disease who had presented to our neuromedicine movement clinic were included in the study. Patients were diagnosed as PD based on UK Parkinson’s disease brain bank criteria. The inclusion criteria were diagnosis as PD, age >18 yrs, inclusion of both males and females and consent for the study. Patients with atypical parkinsonism and secondary parkinsonism, stroke, intake of antipsychotics were excluded from the study. Non motor symptom questionnaire was given to the study group and frequency of occurrence of each non motor symptoms and their predominance in both males and females were studied. The frequency of each NMS was calculated by computing the number of yes response and calculating the percentage related to the number of patients in the sample. Analysis was done to calculate the frequency of all NMS among the enrolled patient.Results: Nocturnal sleep disturbances (43%) were most common followed by constipation (29%).The most common non motor symptoms in males were constipation (20%), urinary urgency (18%) and nocturia (11%).The most common non motor symptoms in females were nocturnal sleep disturbance (25%), feeling sad (19%), unexplained pains (17%) and being anxious (13%).Conclusions: Non motor symptom questionnaire helps in screening patients with Parkinson’s disease of non-motor symptoms and aims at providing holistic treatment improving the quality of life

Biopriming of seeds with microbial biostimulant (Bacillus megaterium ) on improvement of seedling growth, biochemical and root traits of rice (Oryza sativa L.)

This study aimed to evaluate the potential of Bacillus megaterium in improvingseed germination and rice seedling's morpho-physiological andbiochemical traits. The experiment was conducted using a completely randomizeddesign to evaluate the effect of different concentrations of the biostimulantB. megaterium on rice seedlings growth and development undernursery conditions. Biopriming seeds with B. megaterium significantly enhancedseed germination and seedling traits, such as seedling shoot androot length, seedling height, number of leaves, seedling vigor, and shootand root dry biomass, compared to the untreated control. Among the treatments,biopriming seeds with B. megaterium at a concentration of 10g kg-1resulted in the greatest improvements across all the recorded parameters.Root traits such as total root length, surface area, average root diameter,root volume, and root tips and forks were also significantly enhanced. Additionally,biochemical changes like total chlorophyll and soluble protein contentshowed notable improvements with the concentration of B. megaterium. Hence, these results suggest that biopriming seeds with B. megateriumare an efficient strategy to improve seed germination and shoot and rootvigor in rice seedlings

Multi-trait selection indices for identifying elite rice genotypes in rice breeding programs

Rice (Oryza sativa L.) serves as a staple food for nearly half of the global population, with rising demand necessitating significant advancements in productivity. Traditional selection methods that focus solely on yield often fail to account for the complex interplay of agronomic and grain quality traits. The integration of multiple selection indices in breeding enhances efficiency by simultaneously evaluating important traits, aiding in informed decision-making, balancing desirable traits, and accelerating the development of high-performing varieties. This study aimed to evaluate the efficiency of various multi-trait selection indices, namely the Multi-Trait GenotypeIdeotype Distance Index (MGIDI), Genotype by Yield and Trait biplot (GYT), Linear Phenotypic Selection Index (LPSI), and the Elston Index, in identifying elite rice genotypes for breeding programs. A total of 110 genetically diverse rice germplasm lines were evaluated using a randomized block design during the Rabi season of 2023–24. Key agronomic and grain quality traits were assessed, with statistical analyses, including ANOVA and correlation studies, conducted to interpret the result. Among the indices, MGIDI demonstrated the highest selection gains (16.9%) for yield, while other indices demonstrated variable efficiencies across different traits. Traits such as the number of grains per panicle and productive tillers exhibited positively correlations with yield, whereas negative selection for plant height and days to maturity posed challenges. Notably, genotypes BMDK-2-2-8-2, JR 13, A 67, and CR 4376-1-1-1-2-2-1 were consistently selected across indices, reflecting their superior trait performance across multiple traits. Combining several indices improves the breeding process by enabling the selection of genotypes with traits such as nutrient-use efficiency and drought tolerance, thereby improving rice yield under challenging conditions, such as lowfertility soils or drought stress. These findings highlight the importance of multi-trait indices in optimizing genetic gains and improving breeding efficiency. Notably, MGIDI emerged as the most effective tool, providing a comprehensive approach to integrating traits, making it indispensable for rice breeding programs

Exploring gene action and combining ability for yield improve- ment in rice (Oryza sativa L.) landraces

Estimating combining ability is essential for evaluating genotypes and understanding the nature and magnitude of gene actions involved in plant breeding. In a study involving four lines and seven testers, a Line × Tester mating design was employed to analyze combining ability, heterosis, and gene action across 16 yield-related traits. The results indicated significant variances for general combining ability (GCA) and specific combining ability (SCA), underscoring the relevance of additive and non-additive genetic components in trait inheritance. The analysis revealed that the ratio of dominant genetic variance to additive genetic variance was greater than one for most traits, with the exceptions being test weight and the grain length:breadth ratio. This suggests that non-additive gene action predominantly influences the inheritance of the examined traits. Among the parental lines studied, CO 54, CO 55, RL 8601, RL 6298, and RL 27 emerged as the best general combiners for single-plant yield and other traits. Based on the outcomes of standard heterosis, the following hybrid combinations were identified as optimal for augmenting single-plant yield: ADT 58 × RL 2348 (105.33%), CO 55 × RL 6298 (104.5%), CO 54 × RL 6298 (103.87%), CO 54 × RL 8601 (100.76%), ADT 58 × RL 2196 (99.8%), and ADT 56 × RL 6298 (97.65%). These results indicate that the identified cross combinations could be effectively employed in recombination breeding programs focused on producing early-maturing, high-yielding fine-grain rice varieties that align with market requirements

Genetic variability and yield trait associations in F2 populations of traditional rice (Oryza sativa L.) varieties

Analyzing genetic variability and trait correlations is essential for designing effective breeding programs and improving crop characteristics. This study aimed to estimate variability parameters, heritability, genetic advance, skewness, kurtosis, associations, and path coefficients for 13 traits in the F? population derived from the crosses CO 54 × IC 378202 and CO 54 × IC 467496. The cross CO 54 × IC 378202 cross exhibited notable panicle weight with high Genotypic Coefficients of Variation (GCV) (35.94) and Phenotypic Coeffi cients of Variation (PCV) (36.40), elevated Heritability (H2) (97.48), significant Genetic Advance as a Percentage of Mean (GAM) (73.10), and positive skew ness (0.52). Similarly, the CO 54 × IC 467496 cross demonstrated exceptional total tillers per plant, characterized by high Genotypic Coefficients of Varia tion (33.63) and Phenotypic Coefficients of Variation (35.25), substantial Heritability (90.99), notable Genetic Advance as a Percentage of Mean (66.08), and pronounced positive skewness (0.67). In the CO 54 × IC 378202 cross, panicle weight, displayed significant positive correlations (0.641) and direct positive effects (0.2370) on grain yield per plant. Similarly, the CO 54 × IC 467496 cross grains per panicle exhibited strong positive correlations (0.383) and direct effects (0.5360) on grain yield. These findings underscore the significance of panicle weight and grain number per panicle, key deter minants of grain yield, as prime targets for selection in rice breeding pro grams. The observed predominance of additive gene action for these traits suggests their amenability to improvement through pure line selection. By prioritizing these traits, breeders can develop high-yielding rice cultivars, thereby enhancing agricultural productivity and contributing to global food security endeavors

Streamwise-travelling viscous waves in channel flows

The unsteady viscous flow induced by streamwise-travelling waves of spanwise wall velocity in an incompressible laminar channel flow is investigated. Wall waves belonging to this category have found important practical applications, such as microfluidic flow manipulation via electro-osmosis and surface acoustic forcing and reduction of wall friction in turbulent wall-bounded flows. An analytical solution composed of the classical streamwise Poiseuille flow and a spanwise velocity profile described by the parabolic cylinder function is found. The solution depends on the bulk Reynolds number R, the scaled streamwise wavelength (Formula presented.), and the scaled wave phase speed U. Numerical solutions are discussed for various combinations of these parameters. The flow is studied by the boundary-layer theory, thereby revealing the dominant physical balances and quantifying the thickness of the near-wall spanwise flow. The Wentzel–Kramers–Brillouin–Jeffreys (WKBJ) theory is also employed to obtain an analytical solution, which is valid across the whole channel. For positive wave speeds which are smaller than or equal to the maximum streamwise velocity, a turning-point behaviour emerges through the WKBJ analysis. Between the wall and the turning point, the wall-normal viscous effects are balanced solely by the convection driven by the wall forcing, while between the turning point and the centreline, the Poiseuille convection balances the wall-normal diffusion. At the turning point, the Poiseuille convection and the convection from the wall forcing cancel each other out, which leads to a constant viscous stress and to the break down of the WKBJ solution. This flow regime is analysed through a WKBJ composite expansion and the Langer method. The Langer solution is simpler and more accurate than the WKBJ composite solution, while the latter quantifies the thickness of the turning-point region. We also discuss how these waves can be generated via surface acoustic forcing and electro-osmosis and propose their use as microfluidic flow mixing devices. For the electro-osmosis case, the Helmholtz–Smoluchowski velocity at the edge of the Debye–Hückel layer, which drives the bulk electrically neutral flow, is obtained by matched asymptotic expansion

Prospects and challenges of drone technology in sustainable agriculture

Drones have emerged as a viable precision agriculture technology that can help achieve sustainable development goals (SDGs) by enhancing sustainable farming practices, increasing food security and reducing environmental impact. This review paper aims to thoroughly examine the various applications of drone technology, including crop health monitoring, pesticide and fertilizer spraying, weed control and data-driven decision-making for farm optimization. It emphasizes the role of drones in precision spraying, promoting targeted interventions and minimizing environmental impact compared to conventional methods. Drones play a vital role in weed management and crop health assessment. The study emphasizes the relevance of data collected by drones for decision-making concerning irrigation, fertilization and overall farm management. However, using Unmanned aerial vehicles (UAVs) in agriculture faces challenges caused by batteries and their life, flight time and connectivity, particularly in remote areas. There are legal challenges whereby regulatory frameworks and restrictions are present in different regions that affect the operation of drones. With the help of continuous research and development initiatives, the challenges depicted above could be solved and the fullest potential of drones can be tapped for achieving sustainable agriculture

InfoCrop – a crop simulation model for assessing the climate change impacts on crops

This study presents results of evaluation in terms of its validation and impact of climate change on Indian mustard (Brassica juncea), sorghum (Sorghum vulgare) and maize (Zea mays) by using the crop simulation model, ‘InfoCrop’. Simulated results of mustard model showed a spatial variation in yield among all five regions in both irrigated and rainfed mustard. Under irrigated conditions, the yield reduction in 2020, 2050 and 2080 would be highest in Eastern-IGP (Indo-Gangetic Plain) region followed by Central-IGP. This was due to maximum projected rise in temperature in Eastern-IGP where maximum and minimum temperature would rise by 5.1° and 5.6°C in 2080. The reduction of irrigated mustard yield was least in Northern-IGP under almost all scenarios. But in western India, yield reduction gradually increased from 2020 to 2080. In future climate change scenarios, the rainfall would be projected to increase in 2050 irrespective of the locations. But in 2020 and 2080 rainfall would reduce in Northern-IGP, Western and Central India. This was reflected higher yield reduction in rainfed mustard in these three locations. In sorghum, the future climate change scenario analysis showed that the yields (CSH 16 and CSV 15) are likely to reduce at Akola, Anantpur, Coimbatore and Bijapur. But yield of CSH 16 will increase slightly in Gwalior (0.1%) at 2020 and thereafter it will decline. At Kota the sorghum yield is likely to increase in 2020 (3.3 and 1.7 % in CSH 16 and CSV 15 respectively) with no change in 2050 and yields will be reduced at 2080 in both varieties. Maize trend is similar from the sorghum impact except in the UIGP where rainfall could be projected to increase in the future. In MIGP and SP(Southern Plateau), expected reduction would be 5%, 13%, 17% and 21%, 35%, 35% in 2020, 2050 and 2080 respectively from the current level