A fuzzy knowledge-based model for assessing risk of pesticides into the air in cropping systems

Decision support model to assess pesticide safeness toward environment

For farmers around the world to protect crops from disturbing pests, it is common to use pesticides to ward off the growth of pests or even eliminate them. Even though pesticides are seen as a good thing for protecting crops, there is one thing that mustn't be forgotten the origin of the pesticide itself is a toxin compound that is dangerous if used irresponsibly. The main concern of this study is excessive use of pesticides may cause serious consequences to the ecosystem and environment through the accumulation of pesticide residue by irresponsible farmers. To minimize the effects of pesticide residues, the selection of the type of pesticide needs to be considered which type may not be harmful to the environment's health even though accumulation happens. Therefore, in this study, a fuzzy-based computational model assessor was built to measure the safety level of pesticides toward the environment. The fuzzy model was created with consideration of several parameters related to pesticide behaviors, its effects on beneficial organisms, and its persistence in the environment. The method used for this study includes literature reviewing, fuzzification, statistical approach, expert knowledge sharing, and quantitative analysis. The model created in this study can assist in a more accurate and realistic method of selecting better pesticide options that will be used by farmers. To ensure the validity of the model, verifying and validating the formula and pesticide result assessment were done with related literature articles. In this study, from 10 types of pesticides used as a sample, dodine, and iprodione pesticides are the best option for protecting crops with a safety level of 7.36, and abamectin, dimethoate, chorpyrifos, and methidathion are not safe options for farming use because of its potential of harming the environment.

An analysis of the climate change effects on pesticide vapor drift from ground-based pesticide applications to cotton

Vapor drift of applied pesticides is an increasing concern. Among the major crops cultivated in the Lower Mississippi Delta (LMD), cotton receives most of the pesticides. An investigation was carried out to determine the likely changes in pesticide vapor drift (PVD) as a result of climate change that occurred during the cotton growing season in LMD. This will help to better understand the consequences and prepare for the future climate. Pesticide vapor drift is a two-step process: (a) volatilization of the applied pesticide to vapors and (b) mixing of the vapors with the atmosphere and their transport in the downwind direction. This study dealt with the volatilization part alone. Daily values of maximum and minimum air temperature, averages of relative humidity, wind speed, wet bulb depression and vapor pressure deficit for 56 years from 1959 to 2014 were used for the trend analysis. Wet bulb depression (WBD), indicative of evaporation potential, and vapor pressure deficit (VPD), indicative of the capacity of atmospheric air to accept vapors, were estimated using air temperature and relative humidity (RH). The calendar year weather dataset was trimmed to the cotton growing season based on the results of a precalibrated RZWQM for LMD. The modified Mann Kendall test, Pettitt test and Sen's slope were included in the trend analysis suite using 'R'. The likely changes in volatilization/PVD under climate change were estimated as (a) average qualitative change in PVD for the entire growing season and (b) quantitative changes in PVD at different pesticide application periods during the cotton growing season. Our analysis showed marginal to moderate increases in PVD during most parts of the cotton growing season as a result of climate change patterns of air temperature and RH during the cotton growing season in LMD. Estimated increased volatilization of the postemergent herbicide S-metolachlor application during the middle of July appears to be a concern in the last 20 years that exhibits climate alteration.