Search results

The purpose of this study is to assess the quality of honey from different agro-climatic zones of Himachal Pradesh in terms of physicochemical characteristics and mineral status.

Three honey-producing locations were selected within each agro-climatic zone, honey sampled from four separate apiaries within each location and analyzed for physicochemical characteristics and mineral status using standard methodologies. The data were analyzed using one-way analysis of variance with one-way classification, after appropriate transformation through online OP-STAT software and MS Excel. The correlation coefficient (r) was also calculated. Principal component analysis was done using XL-STAT software.

The honey of Zone 4 had highest fructose (36.62%), F:G ratio (1.55), acidity (46.07 meq/kg), vitamin C (25.04 mg/100 g) and diastase (19.22 DN), whereas the pollen density (76,666.67 pollen grains per 10 g), pH (5.94), sucrose (6.94%), hydroxy methyl furfuraldehyde (70.20 mg/kg), amino acid (103.83 mg/100 g), phenols (77.39 mg/100 g), Ca (81.04 mg/kg) and K (354.17 mg/kg) were highest for Zone 2. Highest electrical conductivity (0.24 mS/cm), moisture (16.50 %), glucose (34.20%) and P content (62.93 mg/kg) were recorded for Zone 1. Correlation studies indicated a significant positive correlation between pH and EC; EC and moisture; colour and pollen density. Examining the graphical distribution of the honey samples, a natural separation between honeys of four different agro-climatic zones was obtained.

The impact of geographical/agro-climatic variations in physicochemical characteristics of honey has not been worked out under the present scenario in Himachal Pradesh.

ChatGPT is a new development in this technological era. This artificial intelligence-based tool responds to individuals’ queries and produces the requested content within seconds. Therefore, it is becoming popular among academics, the research community and library professionals. This study aims to test (through personal interaction with the tool) the authenticity of the ChatGPT’s produced records. Another objective of the research is to check the relevance between the individuals’ queries and the tool’s results. The research also intends to identify the challenges in retrieving information through ChatGPT.

The five researchers from different countries and organizations experienced ChatGPT by asking questions on more than 70 subjects. The responses were recorded in Notepad and converted into MS Excel and MS Access to standardize and analyze the data. The investigators consulted 11 reputed databases/sources, including Web of Science and Scopus, to assess the authenticity of the data retrieved through ChatGPT.

The findings confirmed that over 90% of results produced by ChatGPT were fake (the information did not exist in the literature). Similarly, the study sheds light on the discrepancies, such as irrelevant and incomplete information in the data generated by ChatGPT.

This is a unique study that shares the findings based on the different regions’ researchers’ personal experiences with ChatGPT. The researchers covered different subject areas (above 70) while asking questions to ChatGPT. The paper shares implications for researchers, students, faculty members, academic/research organizations and policymakers.