The honey bee (Apis mellifera L.) contributes ∼$17 billion annually to the United States economy, primarily by pollinating major agricultural crops including almond, which is completely dependent on honey bee pollination for nut set. Almond growers face constant challenges to crop productivity owing to pests and pathogens, which are often controlled with a multitude of agrochemicals. For example, fungicides are often applied in combination with other products to control fungal pathogens during almond bloom. However, the effects of fungicides on honey bee health have been so far understudied. To assess the effects of some of the top fungicides used during the 2012 California almond bloom on honey bee forager mortality, we collected foragers from a local apiary and exposed them to fungicides (alone and in various combinations) at the label dose, or at doses ranging from 0.25 to 2 times the label dose rate. These fungicides were Iprodione 2SE Select, Pristine, and Quadris. We utilized a wind tunnel and atomizer set up with a wind speed of 2.9 m/s to simulate field-relevant exposure of honey bees to these agrochemicals during aerial application in almond fields. Groups of 40-50 foragers exposed to either untreated controls or fungicide-laden treatments were monitored daily over a 10-d period. Our results showed a significant decrease in forager survival resulting from exposure to simulated tank mixes of Iprodione 2SE Select, as well as synergistic detrimental effects of Iprodione 2SE Select in combination with Pristine and Quadris on forager survival.
The honey bee (Apis mellifera L. (Hymenoptera: Apidae)) contributes an essential role in the U.S. economy by pollinating major agricultural crops including almond, which depends entirely on honey bee pollination for successful nut set. Almond orchards are often treated with pesticides to control a variety of pests and pathogens, particularly during bloom. While the effects to honey bee health of some insecticides, particularly neonicotinoids, have received attention recently, the impact of other types of insecticides on honey bee health is less clear. In this study, we examined the effects to honey bee forager survival of three non-neonicotinoid pesticides widely used during the 2014 California almond bloom. We collected foragers from a local apiary and exposed them to three pesticides at the label dose, or at doses ranging from 0.5 to 3 times the label dose rate. The selected pesticides included the insect growth regulators methoxyfenozide and pyriproxyfen, and the acaricide bifenazate. We simulated field exposure of honey bees to these pesticides during aerial application in almond orchards by using a wind tunnel and atomizer set up with a wind speed of 2.9 m/s. Experimental groups consisting of 30-40 foragers each were exposed to either untreated controls or pesticide-laden treatments and were monitored every 24 hr over a 10-d period. Our results revealed a significant negative effect of all pesticides tested on forager survival. Therefore, we suggest increased caution in the application of these pesticides in almond orchards or any agricultural crop during bloom to avoid colony health problems.
During the process of plant protection in agriculture, the distribution and deposition of droplets or fog fields could directly influence the effectiveness and efficiency of spray. The traditional method of measurement of the distribution of droplets mainly used water sensitive papers, glass containers or flour to collect data and inverse results, while a new method of measurement based on the principle of reflection of LIDAR was presented. Droplets were the major targets of the study, and four important algorithms were primarily developed, including the recognition and extraction of targets, the superposition in time-domain, the calculation of effective ranges of distribution, and the development of 3D distribution models. Combined with these algorithms, in order to eliminate the environmental noise, the methods of Fuzzy Environment Matching and Secondary Filter were created and utilized. Meanwhile, the statistics was used for analysis of the duration of scanning as well as computation of the distribution, with enough datasets but the minimum length of time. The results of the experiments showed that the relative error of measurement was less than 7% and Relative Standard Deviation was less than 16%, compared with the values of manual measurement. Furthermore, the 3D models were accurate and clarified in the wind-tunnel experiment. The completed system based on this method could adapt to the requirements of both indoor and outdoor detection. Besides, it is capable of the quantized detection of droplet distribution, providing an effective way of tests for spray technique, especially for the research of the application of plant protection by UAVs.
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