Assessment of the pesticidal behaviour of diacyl hydrazine-based ready-to-use nanoformulations

Chemical and Biological Technologies in Agriculture

Table 6 Insect growth regulatory activity of nanoformulations against Spodoptera litura by topical application method

Test formulations	Heterogeneity		Regression equation	b ± SE	R²	GI₉₀ (mg L⁻¹)	Fiducial limit (95% confidence) (mg L⁻¹)
Test formulations	df	χ²	Regression equation	b ± SE	R²	GI₉₀ (mg L⁻¹)	Min	Max
NF1	3	0.999	0.556x + 6.874	0.556 ± 0.366	0.962	0.080	0.017	0.451
1	3	0.997	0.652x + 6.664	0.652 ± 0.290	0.859	0.302	0.081	1.121
NF2	3	1	0.585x + 7.063	0.585 ± 0.362	0.976	0.046	0.009	0.238
NF3	3	1	0.629x + 7.308	0.629 ± 0.357	0.916	0.025	0.005	0.124
NF4	3	0.999	0.749x + 7.507	0.749 ± 0.297	0.962	0.024	0.006	0.090
NF5	3	0.999	0.646x + 7.314	0.647 ± 0.347	0.913	0.024	0.005	0.116
NF6	3	1	0.532x +7.158	0.533 ± 0.426	0.935	0.023	0.003	0.158
NF7	3	1	0.691x + 7.543	0.691 ± 0.339	0.965	0.015	0.003	0.070
7	3	1	0.493x + 6.574	0.493 ± 0.393	0.969	0.262	0.044	1.545
NF8	3	1	0.528x + 7.179	0.529 ± 0.434	0.906	0.021	0.003	0.150
Methoxyfenozide	3	1	0.524x + 6.909	0.524 ± 0.399	0.956	0.065	0.011	0.393

NF nanoformulations, 1: non-nanoparent compound 1, 7: non-nanoparent compound 7 (for further details, please see Pandey et al. [29])
χ²: goodness of fit, b: slope, SE: standard error, R²: regression coefficient. Italics show nanoformulations having highest potential as a nanopesticide