M Massinon, N De Cock, S Ouled Taleb Salah, F Lebeau
{"title":"COMPUTER SIMULATIONS OF SPRAY RETENTION BY A 3D BARLEY PLANT: EFFECT OF FORMULATION SURFACE TENSION.","authors":"M Massinon, N De Cock, S Ouled Taleb Salah, F Lebeau","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>A spray retention model was used in this study to explore theoretically the effect of a range of mixture surface tension on the spray retention and the variability of deposits. The spray retention model was based on an algorithm that tested whether droplets from a virtual nozzle intercepted a 3D plant model. If so, the algorithm determined the contribution of the droplet to the overall retention depending on the droplet impact behaviour on the leaf; adhesion, rebound or splashing. The impact outcome probabilities, function of droplet impact energy, were measured using high-speed imaging on an excised indoor grown barley leaf (BBCH12) both for pure water (surface tension of 0.072 N/m) and a non-ionic super spreader (static surface tension of 0.021 N/m) depending on the surface orientation. The modification of spray mixture properties in the simulations was performed by gradually changing the spray the droplet impact probabilities between pure water and a solution with non-ionic surfactant exhibiting super spreading properties. The plant architecture was measured using a structured light scanner. The final retention was expressed as the volume of liquid retained by the whole plant relative to the projected leaf surface area in the main spray direction. One hundred simulations were performed at different volumes per hectare and flat-fan nozzles for each formulation surface tension. The coefficient of variation was used as indicator of variability of deposits. The model was able to discriminate between mixture surface tension. The spray retention increased as the mixture surface tension decreased. The variability of deposits also decreased as the surface tension decreased. The proposed modelling approach provides a suited tool for sensitivity analysis: nozzle kind, pressure, volume per hectare applied, spray mixture physicochemical properties, plant species, growth stage could be screened to determine the best spraying characteristics maximizing the retention. The model will be further extended with the real droplet trajectories in moving airstreams.</p>","PeriodicalId":10565,"journal":{"name":"Communications in agricultural and applied biological sciences","volume":"80 3","pages":"313-21"},"PeriodicalIF":0.0000,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications in agricultural and applied biological sciences","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A spray retention model was used in this study to explore theoretically the effect of a range of mixture surface tension on the spray retention and the variability of deposits. The spray retention model was based on an algorithm that tested whether droplets from a virtual nozzle intercepted a 3D plant model. If so, the algorithm determined the contribution of the droplet to the overall retention depending on the droplet impact behaviour on the leaf; adhesion, rebound or splashing. The impact outcome probabilities, function of droplet impact energy, were measured using high-speed imaging on an excised indoor grown barley leaf (BBCH12) both for pure water (surface tension of 0.072 N/m) and a non-ionic super spreader (static surface tension of 0.021 N/m) depending on the surface orientation. The modification of spray mixture properties in the simulations was performed by gradually changing the spray the droplet impact probabilities between pure water and a solution with non-ionic surfactant exhibiting super spreading properties. The plant architecture was measured using a structured light scanner. The final retention was expressed as the volume of liquid retained by the whole plant relative to the projected leaf surface area in the main spray direction. One hundred simulations were performed at different volumes per hectare and flat-fan nozzles for each formulation surface tension. The coefficient of variation was used as indicator of variability of deposits. The model was able to discriminate between mixture surface tension. The spray retention increased as the mixture surface tension decreased. The variability of deposits also decreased as the surface tension decreased. The proposed modelling approach provides a suited tool for sensitivity analysis: nozzle kind, pressure, volume per hectare applied, spray mixture physicochemical properties, plant species, growth stage could be screened to determine the best spraying characteristics maximizing the retention. The model will be further extended with the real droplet trajectories in moving airstreams.