Profenophos is a commonly used organophosphate pesticide in pulse crops; however, it is difficult to say whether it is safe from cytogenotoxic effects. Test plant materials (field pea seeds) were soaked in 250 ml of 0.2%, 0.4% and 0.6% profenophos 50% EC separately for 6 hours. The mechanism behind various types of chromosomal anomalies observed due to treatment with profenophos has been discussed in detail.  The effects of the pesticide that appeared in M1 generation diluted in M2. The appearance of C-metaphase with univalent and bivalents, multipolarities, chromatin bridges suggest that these organophosphate pesticides like profenophos affect genetic recombination which may lead to loss of important factors, gain of undesirable characters. This study aims at finding the cytological and genotoxic effect of pesticide profenophos on germ cells of Pisum sativum var. arvense and suggests judicious means of application of pesticides and agrochemicals in appropriate condition to elude further damages in the future.

Cotton is a prominent cash crop cultivated for fiber, edible oil and oil cake. A global environmental issue, like climate change, alters weather parameters necessary for the healthy growth and development of cotton plants, affecting fiber quality and economic yield. The study aims to illustrate the evidence of climate change in Maharashtra and assess its impact on the production of cotton in this region. The study was conducted in the state of Maharashtra, India. Geographic information system (GIS)-based models were created based on the vector data (geopolitical boundaries of the state of Maharashtra and its districts) and the corresponding raster attributes (meteorological data) to examine the changes in the patterns of distribution of temperature, rainfall and severity of drought (Standardized Precipitation Index-SPI) over the study period (1990 to 2015). Further, a statistical multiple linear regression model was developed using district-wise data on yield and climatic parameters obtained from International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) to estimate the relationship between the dependent variable (yield of cotton) and the independent variables (annual rainfall and annual mean temperature). GIS modeling and mapping provide evidence of changes in the spatial distribution of rainfall and temperature. Although the regression analysis seems weak, it is acceptable for natural systems because natural systems are complex and often highly variable, making it difficult to create a perfect model. The multiple linear regression model shows that such changes in climatic parameters have a significant negative impact on the economic yield of cotton.