A new rat model for the study of obesity

The currently used raL models of obesity and diabetes are derived from either Zucker or from Koletsky rats. Recently, we identified a spontaneous obese rat from out Wistar colony which is maintained as an inbred stock for the past 75 years. Initially, one of the male progeny in a litter was observed to have abnormal body weight for its age. The parents of this ral were identified, the progeny selectively bred, and a colony has been developed. This is designated as WNIN-0b. The colony is maintained by mating heterozygous animals (+/ob), as the homozygous (ob/ob) were found to be infertile. The trait is carried as an autosomal recessive mutation and the colony is currenfly in F7 generation.Obesity is visible in these mutants around 35 days of age. They are hyperphagic and reach a body weight of 500—600 g by 105 days of age. “Kinky” tail is characteristic of this mutant and this is visible around 50-60 days. Sexual maturity is delayed in female obese mutants, as judged by the day of vaginal opening. The animals are cuglyccmic and show hyperinsulinaemia, hypertriglyceridaemia, arid hypercholesterolemia. Another mutant showing hyperglycemia is also obtained fromthe obese colony. Unlike earlier models which are essentially derived from a randomAbred stock, this is the first report of a rat obese model, developed spontaneously from an inbred strain

Effect of Collagen type-I on the rate of osseointegration of Ca-containing biodegradable Mg-Zr based alloys

Mg-Zr based biodegradable implants alloyed with Ca were investigated to assess their biocompatibility and efficacy in bone formation and osseointegration. Bare alloys, containing Ca, exhibited low surface energy, poor corrosion-resistance, reduced osteoinduction and bone integration activity. Upon coating with Collagen type-I, these alloys demonstrated enhanced performance as an implant material that are suitable for rapid and efficient new bone tissue induction with optimal mineral content and cellular properties

SELECTIVE CECAL BACTERIAL CHANGES MEDIATE THE ADVERSE EFFECTS ASSOCIATED WITH HIGH PALMOLEIN OR HIGH STARCH DIETS: PROPHYLACTIC ROLE OF FLAX OIL

Objective: Studies on the dynamics of gut bacteria in relation to metabolic adverse effects induced by high palmolein or high starch diets and in relation to health benefits of uncommon foods are lacking. Our aim was to assess under controlled conditions, the impact of vegetable based palmitic acid rich, high fat diet or a high starch diet on various metabolic parameters in relation to selective gut bacterial alterations in rats and also to see the effect of flaxseed oil supplementation on these parameters.Methods: Wistar Rats were fed for 4 mo either a control diet(CT) or a 30% high fat diet (HF) or HF diet with flax oil supplemented at two different doses (HFF1 and HFF2) or a 78% high starch diet (HC) after which they were sacrificed and analyzed for selective cecal bacteria, hematology, immune function and body composition.Results: High palmolein diet fed rats showed a decrease in colony forming units of lactobacillus, enterococci, streptococci bacteria and an increase in enterobacteriaceae in the cecum unlike HC fed rats. While high palmolein diet was found to impair immunity and increase inflammation, high starch diet affected body composition and lipid profile. Supplementing the flax seed oil ameliorated most of the adverse effects of high palmolein diet.Conclusions: Independent of energy intakes both high palmolein and high starch intakes have differential adverse effects. It can be envisaged that the adverse effects of feeding palmolein are mediated through immune impairment and inflammatory response, which in turn are associated with altered gut bacteria profile; and flax oil was found to have a prophylactic role in controlling these adverse effects. This study emphasizes the need to evaluate immunological as well as bacterial profile while assessing the safety of dietary fats in addition to traditional methods.Â

Determinants of Consumer’s Willingness to Pay towards Organic Products: A Structural Equation Modelling Approach

Background: India’s food industries are hotly debated as there are numerous scandals involved in tainted food products, which deliberately lowers the public’s confidence. These incidents made the organic food market growth in developing countries, especially in India. Objective: This study examines the underlying factors that influence consumer’s willingness to pay for organic products. Methods: Coimbatore district of Tamil Nadu in India was purposively selected for the study using a structural equation model (SEM) with 250 respondents. The study was conducted in twelve organic shops distributed across the district. The model is bifurcated into the willingness to pay construct and attitude construct, which helps understand the factors influencing the consumer’s willingness to pay towards organic products. Findings: The results from the attribute construct showed that health concerns, environmental concerns and subjective norms were found to positively affect the consumer’s attitude towards purchasing the organic product. In the case of willingness to pay construct, the factors like attitude, knowledge, awareness and income of the consumers positively influence willingness to pay towards the organic product. In contrast, the factor perceived expensiveness was contrary in nature. Novelty: This empirical study provides a good understanding of purchase intention towards organic products, which will aid the producers, middlemen, and stakeholders develop the product and expand the market

Determinants of Income Diversification among Dairy Farm Households in Tamil Nadu

Dairy farming is the subsidiary occupation for millions of farmers in India. Due to risks and uncertainties in rainfed areas, crop production alone was not much remunerative. Diversifying dairy with the crop and allied activities would generate better income, nutritional security, and regular employment to the farming community and ensure risk reduction. This study investigates the extent and determinants of income diversification among dairy farm households in Tamil Nadu using the Simpson Index of Diversity (SID) and the Tobit regression model. Primary data were collected from dairy farm households during the year 2021-22. The results show that two-thirds of the total household income was shared by on-farm income and the remaining one-third by off-farm and non-farm activities to the total household income. Simpson Index of Diversity (0.38) indicated that the households were diversified with milch animals, but the degree of the diversification was low since high degree of diversification requires more labour and high cost. Further, education, family size, landholding size, herd size, proximity to agricultural or allied industry, access to credit, and membership in farmer producer organizations were the important determinants of income diversification. This study indicates that farm households should adopt a concentric approach that requires targeted research, information dissemination, infrastructure development, and agricultural technical institution establishments to boost income diversification and livelihood

Precision Agriculture Techniques and Practices: From Considerations to Applications

Internet of Things (IoT)-based automation of agricultural events can change the agriculture sector from being static and manual to dynamic and smart, leading to enhanced production with reduced human efforts. Precision Agriculture (PA) along with Wireless Sensor Network (WSN) are the main drivers of automation in the agriculture domain. PA uses specific sensors and software to ensure that the crops receive exactly what they need to optimize productivity and sustainability. PA includes retrieving real data about the conditions of soil, crops and weather from the sensors deployed in the fields. High-resolution images of crops are obtained from satellite or air-borne platforms (manned or unmanned), which are further processed to extract information used to provide future decisions. In this paper, a review of near and remote sensor networks in the agriculture domain is presented along with several considerations and challenges. This survey includes wireless communication technologies, sensors, and wireless nodes used to assess the environmental behaviour, the platforms used to obtain spectral images of crops, the common vegetation indices used to analyse spectral images and applications of WSN in agriculture. As a proof of concept, we present a case study showing how WSN-based PA system can be implemented. We propose an IoT-based smart solution for crop health monitoring, which is comprised of two modules. The first module is a wireless sensor network-based system to monitor real-time crop health status. The second module uses a low altitude remote sensing platform to obtain multi-spectral imagery, which is further processed to classify healthy and unhealthy crops. We also highlight the results obtained using a case study and list the challenges and future directions based on our work