Development of a predictive uptake model to rationalise selection of polyoxyethylene surfactant adjuvants for foliage-applied agrochemicals

Autor: B. Terence Grayson, Peter J. Holloway, David Stock, Paul Whitehouse
Rok vydání: 1993
Předmět:
Zdroj: Pesticide Science. 37:233-245
ISSN: 0031-613X
DOI: 10.1002/ps.2780370302
Popis: Composition-concentration relationships between a series of C13/C14 polyoxyethylene primary alcohol (AE) surfactants and the foliar uptake enhancement of five model neutral organic compounds were examined in factorially designed experiments on wheat (Triticum aestivum L.) and field bean (Vicia faba L.) plants grown under controlled environment conditions. Model compounds were applied to leaves as c.0.2-μl droplets of 0.5 g litre−1 solutions in aqueous acetone in the absence or presence of surfactants at 0.2, 1 and 5g litre−1. Uptake of the highly water-soluble compound, methylglucose (log octanol-water partition coefficient (P) = - 3.0) was best enhanced by surfactants with high E (ethylene oxide) contents (AE15, AE20), whereas those of the lipophilic compounds, WL110547 (log P = 3.5) and permethrin (log P = 6.5), were increased more by surfactants of lower E contents, especially AE6. However, there was little difference between AE6, AE11, AE15 and AE20 in their ability to promote uptake of the two model compounds of intermediate polarity, phenylurea (log P = 0.8) and cyanazine (log P = 2.1). Absolute amounts of compound uptake were also influenced strongly by both surfactant concentration and plant species. Greatest amounts of uptake enhancement were often observed at high surfactant concentration (5 g litre−1) and on the waxy wheat leaves compared with the less waxy field bean leaves. The latter needed higher surfactant thresholds to produce significant improvements in uptake. Data from our experiments were used to construct a simple response surface model relating uptake enhancement to the E content of the surfactant added and to the physicochemical properties of the compound to be taken up. Qualitative predictions from this model might be useful in rationalising the design of agrochemical formulations.
Databáze: OpenAIRE