Pesticide Sources to the Soil and Principles of Spray Physics

Himel, Chester M.; Loats, H.L.; Bailey, George W.

doi:10.2136/sssabookser2.c2

Cited by 11 publications

(6 citation statements)

References 33 publications

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“…Moreover, pollen groups from the same locations displayed consistent differences in concentrations and tPHQ values. Pesticides can reach the area outside crops by drift during and after spraying and by volatilization from soil and plant surface (Himel et al, 1990), generating pesticide-enriched rainfalls (Jensen et al, 2007), and atmospheric dust deposition (Wheatley, 1973). Spray drift is a mechanism of pesticide droplets moving through air or water (Felsot et al, 2010), and a constant concern of pesticide use (Damalas, 2015).…”

Section: Discussionmentioning

confidence: 99%

Botanical Origin of Pesticide Residues in Pollen Loads Collected by Honeybees During and After Apple Bloom

Favaro

Bauer

Rossi³

et al. 2019

Front. Physiol.

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Honeybees closely rely on insect-pollinated plants for their survival. Each forager bee displays a tendency of loyalty toward specific plant species during the many daily foraging flights. Due to the ease of collection, pollen loads have been extensively used as a proxy for detection of pesticide residues. Pollen is the main protein food source for colonies, and its contamination has also been addressed as a reason for the colony losses phenomenon. As honeybees fly over a variable but wide range territory, they might collect pollen from both agricultural, urban and wild environments, also displaying considerable preferences in botanical sources between colonies of the same apiary. It is thus difficult to address the source of the pesticide contamination, when pollen is analyzed as a whole. In the current study, a practical and reliable approach has been proposed to narrow down the source of contamination. Pollen loads have been collected from colonies placed in eight locations over large apple orchard extensions in Trentino-South Tyrol region (Italy), during and 2 weeks after apple blossom. The pollen loads have been separated by the color due to the predominant plant species. On each color group, palynology and multi-residual chemical analyses have been performed in parallel. The pollen hazard quotient (PHQ) was used to estimate the risk to honeybees of each color group and of the total collected pollen. Apple and dandelion pollen were the main portions of the first collection, while a greater variety emerged after the apple blossom. Dandelion was always present in the samples. The frequency and the amount of pesticide residues differed according to the collection periods, the locations and the pollen color groups. The amount of insecticide residues increased after the apple blossom, while no difference between the period was found on fungicide residues. The PHQ values were higher after the blossom due to the insecticide contribution, with highest values of 160,000 and 150,000. The variations within samples did not allow to identify a unique source of contamination, whereas it seems that the pollen from plants outside the agricultural areas has as much residues as the pollen from apple orchards.

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Section: Discussionmentioning

confidence: 99%

Botanical Origin of Pesticide Residues in Pollen Loads Collected by Honeybees During and After Apple Bloom

Favaro

Bauer

Rossi³

et al. 2019

Front. Physiol.

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“…The flight paths of the droplets according to AGDISP without the wind [37] Fig. 20. The flight paths of the droplets according to AGDISP with the wind [37] From the given previously Figures one can guess immediately, that the picture of trajectories, according to CFD, contrary to AGDISP predictions, is quite different and the CFD model gives the trajectories more disturbed by the wind and without so explicit swirling shape.…”

Section: Resultsmentioning

confidence: 87%

“…During the same period, other researchers independently developed their own spray-drift models or contributed essential parts of the modeling process. These models are shown in [45,3,42,16,2,17,20,34,43].…”

Section: Introductionmentioning

confidence: 99%

CFD Analysis of the Fluid Particles Distribution by Means of Aviation Technique

Seredyn

Dziubiński

Jaśkowskí³

2018

Transactions on Aerospace Research

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The article describes a computational study, using CFD models, of droplet spray dispersal in the wake of a ‘Turbo Kruk’ airplane up to 500 m downstream. The CFD Reynolds-averaged Navier-Stokes (RANS) models use a Lagrangian (droplet phase) and Eulerian (fluid phase) procedure to predict the droplet trajectories trough the turbulent aircraft wake. The methods described in the work have the potential to improve current models for aerial spraying and will help in the development of new spraying procedures. In this study, the CFD models are used to describe the phenomenon of sprays released from atomizers mounted on the plane. A parametric study of the aircraft model examines the effects of crosswind on the aircraft’s vortex structures and the resulting droplet trajectories. The study shows, that such influence is underestimated in the current models. A comparison of the present results to AGDISP predictions is provided.

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“…They did indicate that E. muricata may have some long hairs at the base of the leaf blades, but this characteristic was not observed in the current study. Leaf hairs may directly influence the retention and uptake of herbicides (Himel et al 1990). For instance, Sterling and Jochem (1999) found that the white locoweed (Oxytropis sericea Nutt.…”

Section: Phenotypic Differentiation Within and Among Echinochloa Ecotypesmentioning

confidence: 99%

Morphophysiological diversity and its association with herbicide resistance in Echinochloa ecotypes

et al. 2021

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The genus Echinochloa constitutes some of the most prominent weed species found in rice (Oryza sativa L.) production worldwide. The taxonomy of Echinochloa is complex due to its morphological variations. The morpho-physiological diversity and taxonomic characteristics of Echinochloa ecotypes infesting rice fields in Texas are unknown. A total of 54 Echinochloa ecotypes collected during late-season field surveys in 2015 and 2016 were characterized in a common garden in 2017. Plants were characterized for 14 morpho-physiological traits including stem angle; stem color; plant height; leaf color; leaf texture; flag leaf length, width, and angle; days to flowering; panicle length; plant biomass; seed shattering; seed yield; and seed dormancy. Principal component analysis indicated that four (plant height, flag leaf length, seed shattering, and seed germination) of the 14 phenological traits characterized here had significantly contributed to the overall morphological diversity of Echinochloa spp. Results showed wide inter-population diversity for the measured traits among the E. colona ecotypes, as well as diverse intra-population variability in all three Echinochola species studied, including barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.], junglerice [Echinochloa colona (L.) Link], and rough barnyardgrass [Echinochloa muricata (P. Beauv.) Fernald]. Taxonomical classification revealed that the collection consisted of three Echinochloa species, with E. colona being the most dominant (96%), followed by E. crus-galli (2%), and E. muricata (2%). Correlation analysis of morpho-physiological traits and resistance status to commonly used preemergence (clomazone, quinclorac) and postemergence herbicides (propanil, quinclorac, imazethapyr, and fenoxaprop-ethyl) failed to show any significant association. Findings from this study provided novel insights into the morpho-physiological characteristics of Echinochloa ecotypes in rice production in Texas. The morphological diversity currently present in Echinochloa ecotypes could contribute to their adaptation to selection pressure imposed by different management tools, emphasizing the need for a diversified management approach to effectively control this weed species.

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Pesticide Sources to the Soil and Principles of Spray Physics

Cited by 11 publications

References 33 publications

Botanical Origin of Pesticide Residues in Pollen Loads Collected by Honeybees During and After Apple Bloom

Botanical Origin of Pesticide Residues in Pollen Loads Collected by Honeybees During and After Apple Bloom

CFD Analysis of the Fluid Particles Distribution by Means of Aviation Technique

Morphophysiological diversity and its association with herbicide resistance in Echinochloa ecotypes

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