We tested seven contemporary agrochemicals as potential plant protectants against ozone phytotoxicity. In nine experiments, Bel-W3 tobacco plants were experienced weekly exposures to a) 80 nmol mol−1 of ozone-enriched or ozone-free air in controlled environment chambers, b) an urban air polluted area, and c) an agricultural-remote area. Ozone caused severe leaf injury, reduced chlorophylls' and total carotenoids' content, and negatively affected photosynthesis and stomatal conductance. Penconazole, (35% ± 8) hexaconazole (28% ± 5) and kresoxim-methyl (28% ± 15) showed higher plants’ protection (expressed as percentage; mean ± s.e.) against ozone, although the latter exhibited a high variability. Azoxystrobin (21% ± 15) showed lower protection efficacy and Benomyl (15% ± 9) even lower. Trifloxystrobin (7% ± 11) did not protect the plants at all. Acibenzolar-S-methyl + metalaxyl-M (Bion MX) (−6% ± 17) exhibited the higher variability and contrasting results: in some experiments it showed some protection while in others it intensified the ozone injury by causing phytotoxic symptoms on leaves, even in control plants.

The research was conducted to evaluate in-vitro efficacy of numerous fungicides against Fusarium oxysporum f. sp. capsici. In present research, six treatments (T) viz. Carbendazim, Benomyl, Topsin-M, Difenoconazole, Nativo, and Alliete along with control, various concentrations (C), days (D), and their interactions, i.e., (T × C), (T × D), (C × D), and (T × C × D) were exploited in a laboratory through food poison technique. Alliete expressed maximum colony growth (1.93 cm) as compared to all other fungicides with respect to control. Interaction between treatments and concentration (T × C) exhibited maximum colony growth of all treatments (Carbendazim, Benomyl, Topsin-M, Difenoconazole, Nativo, and Alliete), i.e., 0.87, 1.23, 1.73, 2.20, 2.53, and 2.93 cm at 300 ppm as compared to 500 and 700 ppm concentrations, respectively. Similar trend was also observed concerning interaction between (fungicides × days) and (tested concentrations × days). Results of the present study revealed that among tested fungicides, Carbendazim at 700 ppm expressed significant reduction in fungal growth.

Benzimidazole fungicides (BFs) are a type of pesticide of high environmental interest characterized by a heavy fluorescence spectral overlap which complicates its detection in mixtures. In this paper, we present a computational study based on supervised neural networks for a multi-label classification problem. Specifically, backpropagation networks (BPNs) with data fusion and ensemble schemes are used for the simultaneous resolution of difficult multi-fungicide mixtures. We designed, optimized and compared simple BPNs, BPNs with data fusion and BPNs ensembles. The information environment used is made up of synchronous and conventional BF fluorescence spectra. The mixture spectra are not used in the training nor the validation stage. This study allows us to determine the convenience of fusioning the labels of carbendazim and benomyl for the identification of BFs in complex multi-fungicide mixtures.