Socio-economic determinants of Dairy Farmers’ Knowledge on Dairy Farming Practices in Uttar Pradesh, India

The study was carried out among dairy farmers of Balamau block of Hardoi district of Uttar Pradesh to assess the socio-economic landscape and dairy farming practices. Utilizing a multistage purposive cum random sampling approach, data from 60 dairy farmers were collected and analyzed. Findings revealed diverse socio-economic backgrounds and educational levels among farmers, influencing their farming decisions. Buffalo predominated the livestock, with significant variations in milk production of cross breeds. Reproductive parameters underscored opportunities for improvement. Correlation and regression analyses elucidated education, training participation, social participation and scientific orientation as pivotal predictors of knowledge level in dairy management. Higher education and greater participation in training sessions were associated with better management practices. The study emphasizes the significance of education, continuous learning and scientific orientation in optimizing dairy farming practices and enhancing industry profitability offering valuable insights for stakeholders in the field. Regression analysis explained 62.10% of knowledge variation, emphasizing education, family type, training, social participation, and scientific orientation

Fuzzy C-Means Clustering with Histogram based Cluster Selection for Skin Lesion Segmentation using Non-Dermoscopic Images

Purpose – Pre-screening of skin lesion for malignancy is highly demanded as melanoma being a life-threatening skin cancer due to unpaired DNA damage. In this paper, lesion segmentation based on Fuzzy C-Means clustering using non-dermoscopic images has been proposed. Design/methodology/approach – The proposed methodology consists of automatic cluster selection for FCM using the histogram property. The system used the local maxima along with Euclidean distance to detect the binomial distribution property of the image histogram, to segment the melanoma from normal skin. As the Value channel of HSV color image provides better and distinct histogram distribution based on the entropy, it has been used for segmentation purpose. Findings – The proposed system can effectively segment the lesion region from the normal skin. The system provides a segmentation accuracy of 95.69 % and the comparative analysis has been performed with various segmentation methods. From the analysis, it has been observed that the proposed system can effectively segment the lesion region from normal skin automatically. Originality/Value – This paper suggests a new approach for skin lesion segmentation based on FCM with automatic cluster selection. Here, different color channel has also been analyzed using entropy to select the better channel for segmentation. In future, the classification of melanoma from benign naevi can be performed

Mössbauer, XRD and TEM Study on the Intercalation and the Release of Drugs in/from Layered Double Hydroxides

Layered double hydroxides (LDHs) are one of the very important nano-carriers for drug delivery, due to their many advantageous features, such as the ease and low-cost of preparation, low cytotoxicity, good biocompatibility, protection for the intercalated drugs, and the capacity to facilitate the uptake of the loaded drug in the cells. In our previous studies, Mössbauer spectroscopy was applied to monitor structural changes occurring during the incorporation of Fe(III) in MgFe- and CaFe-LDHs, and the intercalation of various organic compounds in anionic form. Recently, we have successfully elaborated a protocol for the intercalation and release of indol-2-carboxylate and L-cysteinate in CaFe-LDH. The corresponding structural changes in the LDH samples were studied by XRD, HR-TEM and 57Fe Mössbauer spectroscopy. The Mössbauer spectra reflected small but significant changes upon both the intercalation and the release of drugs. The changes in the basal distances could be followed by XRD measurements, and HR-TEM images made these changes visible

MODE OF DRYING THE NANOPARTICLES AND IT’S STABILITY OF THE FERROFLUIDS

Bare and oleic acid capped magnetite nanoparticles were obtained by coprecipitation method. Ferrofluids were prepared by dispersing bare and oleic acid capped magnetite (dried at room temperature and 80 oC) nanoparticles in H2O and ethylene glycol (EG). Ferrofluids prepared by non-polar solvent i.e. ethylene glycol is found to be more stable than the one prepared by a polar solvent. Among the ferrofluids prepared in EG, the oleic acid capped nanoparticles dried at 80 oC settles in less interval of time. The interaction of the nanoparticles resulting to agglomeration is discussed in details

Effect of integrated nutrient management on growth, flowering and yield of African marigold (Tagetes erecta L.) Cv. Pusa Basanti Gainda

According to the result of the current study, plant height, canopy, stem girth, number of primary branches and total dry matter of the plant at 30 DAT, 60 DAT, 90 DAT were recorded maximum with the application of 100% RDF. The maximum yield parameters, such as a number of flowers per plant, yield/plant, yield/plot and yield/ha., flowering parameters, such as minimum days to first flower bud appearance, 50% flowering, first harvest and maximum flowering duration, i.e., the highest gross return/ha and the net return/ha were recorded highest by the application of 75% RDF + Vermicompost (1.25t/ha)

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Not AvailableRainfall being a complex phenomenon governed by various meteorological parameters is difficult to model and forecast with high precision. For hilly regions such as state of Sikkim and adjoining areas of West Bengal, rainfall acts as lifeline. Several parametric models such as seasonal autoregressive integrated moving average (SARIMA) and exponential autoregressive (EXPAR) are very popular and extensively used to model and forecast rainfall. Owning to complex nature of rainfall series, non-parametric time delay neural network (TDNN) model has also gained substantial amount of attention by researchers. This study uses these two broad class of models and applies them to the monthly rainfall of Sub-Himalayan West Bengal and Sikkim. The models were compared based on their forecasting efficiencies and pattern prediction ability.Not Availabl