Abstract In the Agriculture sector, the farmers need a reliable estimation for pre-harvest crop yield prediction to decide their import-export policies. The present work aims to assess the impact of remote sensing-based derived products with Climate data on the accuracy of a prediction model for the sugarcane yield. The regression method was used to develop an empirical model based on VCI, Historical Sugarcane Yield, and Climatic Parameters of 75 districts of six major sugar-producing states of India. The MOD13Q1 product of MODIS on Board Terra Satellite at 16-day intervals was accessed during the growing season of sugarcane crop with 36 meteorological parameters for experimentation. The accuracy of the model was evaluated using R2, Root Mean square Metric (RMSE), Mean Absolute Error (MAE), and mean square error (MSE). The preliminary results concluded that the proposed methodology achieved the highest accuracy with (R2 =0.95, MAE=5.18, MSE=34.5, RMSE=5.87). The conclusion of the study highlighted that the coefficient of determination can be improved significantly by incorporating maximum and minimum temperature parameters with Remote sensing derived vegetation indices for the sugarcane yield.

Abstract Sharing digital images on social media has become very common these days. People must check for authenticity to share images on social media websites. The shared image may be forged intentionally or unintentionally and can defame someone's reputation, leading to severe events, such as public riots. Thus, authentication of digital images which are posted on social media websites is of paramount importance. Our social media should be intelligent enough to check on these forged images such that no false information spreads around society. Many image forgery detection algorithms have been used by big social groups based on JPEG compression artifacts, but these may not work well in the presence of anti-forensics. JPEG compression is the most widely used standard in social media these days. Two important artifacts, quantization and blocking artifacts, are being exploited by various experts for forensic analysis. JPEG anti-forensic techniques clear away these artifacts to fool forensic detectors. This work presents a novel technique derived from the inter-block interdependence of DCT coefficients for ferreting out JPEG-blocking artifacts in the presence of anti-forensics. In the case of JPEG images, the cropping operation shifts the blocking artifacts within the block, changing the inter-block interdependence. We propose to take advantage of this change to ferret out the blockiness in an image that will help the forensic analyst detect forgery. The proposed method can detect blocking artifacts even if anti-forensic operations are applied and take the intelligence of social media to a step up. A set of different and reproducible experiments have been conducted over a large set of images. It has been observed that the proposed detector outperformed the existing ones in ferreting out blocking artifacts in altered (anti-forensically) JPEG images.

Abstract In neonates, rapid change in diet imbalances gut health allowing colonization of opportunistic pathogens that confer harmful effects on animal health causing reduced digestion and malabsorption of nutrients. In this milieu, probiotic feeding can be a promising approach in promoting animal health and stabilization of gastrointestinal microbiota. Hence, the present study was designed to investigate the effect of Lactobacillus acidophilus NCDC15 enriched fermented milk on nutrient digestibility, faecal biomarkers and immune response in Murrah buffalo calves. Twenty-four, neonatal calves (5-7 days) were randomly allocated into four groups for 90 days. The control group (CT) was provided a basal diet of calf starter and green fodder (maize and jowar), without any probiotic fermented milk (PFM) supplementation. Basal diet was supplemented with probiotic fermented milk at 100, 200 and 300 mL/calf/day, in PFM100, PFM200 and PFM300 groups, respectively. Nutrient digestibility remained similar among the groups. Faecal acetate was higher (P<0.05) in PFM200 and PFM300, while, faecal butyrate was increased (P<0.05) with all levels of probiotic supplementation than control. Faecal Lactobacillus and Bifidobacterium count were increased (P<0.05) with a concomitant reduction in coliform population (P<0.05) among all the treatments. Cell-mediated and humoral immune response were higher (P<0.001) in PFM200 and PFM300 than CT. Overall, it can be concluded that inclusion of Lactobacillus acidophilus NCDC15 in the form of fermented milk upto 300 mL/calf/day improved immunity and faecal biomarkers in Murrah buffalo calves without any adverse effect on nutrient utilization which may positively impact growth performance in Murrah buffalo calves.

The aim of the present work was to study a simple colorimetric and potentiometric biosensor based on urease inhibition by Pb (II) ions for its estimation in milk samples. Urease immobilized on nylon membrane by hydrosol gel method was used as the biocomponent to demonstrate the metal effect on the enzyme activity using phenol red as the pH indicator. A lower limit detection of 38.6µm was achieved in the milk and the enzyme membranes were stable for more than two months at 4ºC. In potentiometric approach, response of an ion selective electrode (ISE) to changing ammonium ion concentration as a consequence of urease inhibition by Pb (II) ions was explored to achieve a detection limit of 9.66 µm. Lead specificity was attained by means of masking agents 1,10 - phenanthroline and sodium potassium tartarate. Validation of the developed biosensors was carried out with spiked milk samples.

Thermal degradation of waste plastics in an inert atmosphere has been regarded as a productive method, because this process can convert waste plastics into hydrocarbons that can be used either as fuels or as a source of chemicals. In this work, waste high-density polyethylene (HDPE) plastic was chosen as the material for pyrolysis. A simple pyrolysis reactor system has been used to pyrolyse waste HDPE with the objective of optimizing the liquid product yield at a temperature range of 400ºC to 550ºC. Results of pyrolysis experiments showed that, at a temperature of 450ºC and below, the major product of the pyrolysis was oily liquid which became a viscous liquid or waxy solid at temperatures above 475ºC. The yield of the liquid fraction obtained increased with the residence time for waste HDPE. The liquid fractions obtained were analyzed for composition using FTIR and GC-MS. The physical properties of the pyrolytic oil show the presence of a mixture of different fuel fractions such as gasoline, kerosene and diesel in the oil.