Economic Evaluation of Pesticide Use Externalities in the Cotton Zones of Punjab, Pakistan

The crop protection strategy in Pakistan is almost entirely based on pesticide use whereas development of integrated pest management (IPM) based technologies is in its initial phases of scrutiny as well as implementation. The inefficient use of chemicals has resulted in environmental pollution and sub-optimal returns to the society on the costly investments. This study estimates the social cost of pesticide use and suggests appropriate guidelines for regulating the safe use of pesticides. An overall economic evaluation of the externalities for the current pesticide use levels shows that external costs are quite higher than the currently paid price at the farm gate level. The environmental degradation and public health costs inflicted on the society due to the inefficient chemical use on cotton crop amounts to twelve thousand million rupees. The reduced reliance on crop protection through chemical methods seems inevitable for a sustainable and healthy crop production.economic evaluation; externalities; pesticide use; social cost; crop protection; Punjab; Pakistan

Economic Evaluation of Pesticide Use Externalities in the Cotton Zones of Punjab, Pakistan

The crop protection strategy in Pakistan is almost entirely based on pesticide use whereas development of integrated pest management (IPM) based technologies is in its initial phases of scrutiny as well as implementation. The inefficient use of chemicals has resulted in environmental pollution and sub-optimal returns to the society on the costly investments. This study estimates the social cost of pesticide use and suggests appropriate guidelines for regulating the safe use of pesticides. An overall economic evaluation of the externalities for the current pesticide use levels shows that external costs are quite higher than the currently paid price at the farm gate level. The environmental degradation and public health costs inflicted on the society due to the inefficient chemical use on cotton crop amounts to twelve thousand million rupees. The reduced reliance on crop protection through chemical methods seems inevitable for a sustainable and healthy crop production

Ambient-noise Free Generation of Clean Underwater Ship Engine Audios from Hydrophones using Generative Adversarial Networks

Generative adversarial networks (GANs) have been extensively used in image domain showing promising results in generating and learning data distributions in the absence of clean data. However, the audio domain, specially underwater acoustics are not yet fully explored in reporting the efficiency and applicability of GANs. We propose an audio GAN framework called ambient noise-free GAN (AN-GAN) to address the underwater acoustic signal denoising problem by removing the background ambient noise. The proposed AN-GAN can learn a clean audio generation with improved signal-to-noise ratio (SNR) given only the noisy samples from the underwater audio dataset. The simulated and real-time data collected from online available source ShipsEar, is used for the analysis and validation purpose. The comparative analysis shows an average percentage improvement of proposed AN-GAN with GAN-based and conventional statistical underwater denoising methods as 6.27% for UWAR-GAN, 227% for Wavelet denoising, 247% for EMD and 65% for Wiener technique

Viable forecasting monthly weather data using time series methods

The main object of the research was to assess the forecast values of the weather parameters by using three-time series methods such as Decomposition of time series, Autoregressive (AR) model with seasonal dummies and Autoregressive moving average (ARMA) /Autoregressive Integrated moving average (ARIMA) model. A recent phenomenon in weather changing has disturbed the world in general and Pakistan in particular. In Pakistan due to climate change, flood and heat stroke have taken many lives. Stationarity was measured through the Augmented Dickey-Fuller test; results showed that some variables are I(0) and some are I(1). The reliability of the forecast results was examined through the goodness of fit test. For finding the best fit model, the performance measures of various models: Root Mean Squire Error, Mean Absolute Error and Mean Absolute Percentage Error were considered. The model in which the above statistics are the minimum was chosen as the appropriate model. After model analysis and validation, it was observed that AR-model with seasonal dummies was found to be the best fit model between the three models. Meanwhile, the forecasting for the period Jan.2018 to Dec.2018 was made based on the best fit model. Given the future forecasting results, the temperature will be normal at selected stations. The wind and rainfall will also be present. Overall, it was suggested that the obtained findings of meteorological stations' weather might be normal for the coming few months over there, and no chance of heatstroke and flood might be expected. Future studies must be carried out to provide the awareness to well-being regarding ecological hazardous to minimize their economic loss through mass media

Preliminary selection and evaluation of fungicides and natural compounds to control grey mold disease of rose caused by Botrytis cinerea

Botrytis cinerea es un hongo patógeno de las plantas que causa la enfermedad del moho gris del rosal (Rosa indica L.). La búsqueda de estrategias de control nuevas y alternativas respetuosas con el medio ambiente, en lugar de los productos químicos peligrosos, para diferentes enfermedades de los cultivos es un paso crucial y saludable para hacer frente a los retos actuales del cambio climático. Por lo tanto, este estudio tuvo como objetivo evaluar la eficacia de diferentes extractos botánicos y agentes de biocontrol (biopesticidas) junto con diferentes fungicidas contra B. cinerea en condiciones in vitro. Se utilizaron tres concentraciones diferentes, a saber, 100, 200 y 300 ppm de cinco fungicidas, a saber, Acrobate, Melody, Cabrio top, Antracol y oxicloruro de cobre, extractos botánicos de ocho plantas Dhatura, Jengibre, Aak, Neem y Cebolla, en tres dosis diferentes de 5, 10 y 15%, El estudio de la incidencia de la enfermedad% de moho gris en el cultivo de rosas en la región muestra que la región de Hyderabad tiene un máximo (60%) de incidencia de la enfermedad en comparación con la región de Tandojam (40%). Entre los fungicidas, el Cabrio top redujo significativamente el crecimiento lineal de colonias (31 mm) de B. cinerea a una concentración de 300 ppm. Entre los productos botánicos, el extracto de la planta de neem mostró significativamente el menor crecimiento de colonias (23,33 mm), seguido de la planta de jengibre (25 mm) y la planta de dhatura (26 mm). La mayor concentración de fungicidas y las dosis más altas (15%) de extractos botánicos resultaron significativamente eficaces para controlar el patógeno B. cinerea. Among biopesticides, Fusarium solani appeared prominent in reducing colony growth (25.16 mm) of the pathogen but the difference was not significant 300 with most of the tested biocontrol agents. La recomendación en este estudio es la alta capacidad de los extractos botánicos y agentes de biocontrol en la reducción del crecimiento de moho gris, considerando potencialmente su uso en lugar de fungicidas sintéticos y mayor seguridad para el ecosistema.Campus Ic

Design and Fabrication of a Robust Chitosan/Polyvinyl Alcohol-Based Humidity Sensor energized by a Piezoelectric Generator

Due to their rapid growth in industrial and environmental applications, there is a need to develop self-powered humidity sensor systems with improved sensitivity, a wide detection range, and an eco-friendly nature. In this study, an aqueous solution of chitosan (CS) and polyvinyl alcohol (PVA) was blended to yield a composite film material with enhanced humidity detection properties. Meanwhile, a polyvinylidene difluoride (PVDF)-loaded chitosan composite film was developed and employed as a piezoelectric generator. Moreover, the developed composite materials for both devices (the piezoelectric generator and the humidity sensor) were optimized based on output performance. The piezoelectric generator generates a maximum of 16.2 V when a force of 10 N is applied and works as a power source for the humidity-sensing film. The sensing film swells in response to changes in relative humidity, which affects film resistance. This change in resistance causes a change in voltage through the piezoelectric generator and allows the precise measurement of relative humidity (RH). The fabricated sensor showed a linear response (R2 = 0.981) with a reasonable sensitivity (0.23 V/% RH) in an environment with an RH range of 21–89%. In addition, the device requires no external power, and therefore, it has numerous sensing applications in various fields

Design and Fabrication of a Robust Chitosan/Polyvinyl Alcohol-Based Humidity Sensor energized by a Piezoelectric Generator

Due to their rapid growth in industrial and environmental applications, there is a need to develop self-powered humidity sensor systems with improved sensitivity, a wide detection range, and an eco-friendly nature. In this study, an aqueous solution of chitosan (CS) and polyvinyl alcohol (PVA) was blended to yield a composite film material with enhanced humidity detection properties. Meanwhile, a polyvinylidene difluoride (PVDF)-loaded chitosan composite film was developed and employed as a piezoelectric generator. Moreover, the developed composite materials for both devices (the piezoelectric generator and the humidity sensor) were optimized based on output performance. The piezoelectric generator generates a maximum of 16.2 V when a force of 10 N is applied and works as a power source for the humidity-sensing film. The sensing film swells in response to changes in relative humidity, which affects film resistance. This change in resistance causes a change in voltage through the piezoelectric generator and allows the precise measurement of relative humidity (RH). The fabricated sensor showed a linear response (R2 = 0.981) with a reasonable sensitivity (0.23 V/% RH) in an environment with an RH range of 21–89%. In addition, the device requires no external power, and therefore, it has numerous sensing applications in various fields