Evaluating farmer's satisfaction of different agrotextile bunch covers using desirability function

Abstract

This paper deals with an evaluation of farmer's satisfaction of agrotextile as a date bunch cover using global quality index. Referring to literature studies, desirability function remains an appropriate method that allows a level of flexibility over graphical tool in defining and evaluating quality. The application of desirability function is discussed and investigated. Using a statistical survey based on Tunisian farmers, it was concluded that ideal bagging product depends on date bunch requirements, weight and goal of each individual agrotextile cover's property. Based on a comparative analysis, the desirability function remains sufficient to objectively classify different bags for protection of date palm. Useful index values have been found and can be used by farmers or industries to accurately predict the quality of date bunch cover and to select the best supplier to launch the needed order. In this work, the fabrics that have been considered are woven, knitted and nonwoven fabrics. Nonwoven products are used for the first time in the palm field and have been evaluated in this paper. The results show that nonwoven products were closer to the desired performance compared to knitted and woven fabrics.

Recycled PVC content and particle size distribution effects on morphological and mechanical properties of expanded PVC layer for floorcoverings

“…The desirability function approach is one of the most widely used methods in industry for the optimization of multiple-response processes [40]. For each response Y i (x), a desirability function d i (Y i (x)) assigns numbers between 0 and 1 to the possible values of Y i [40][41][42][43][44][45]. Different functions may be built, depending on the optimization criteria adopted, within an acceptable range of response values given by (U i − L i ), where U i is the upper acceptable value for the response and L i is the lower.…”

“…Different functions may be built, depending on the optimization criteria adopted, within an acceptable range of response values given by (U i − L i ), where U i is the upper acceptable value for the response and L i is the lower. Thus, if the response has to be maximized, d i (Y i (x)) is described by the following equation [43][44][45]:…”

“…Finally, when a target value T i (with L i ≤ T i ≤ U i ) is the most desirable response, the function is given by [43][44][45]:…”

“…The weighting coefficients (r i ) are used to emphasize certain parameters over others, depending on their significance in determining the overall quality [43][44][45].…”