More than 10 years after commercialization, Vip3A-expressing MIR162 remains highly efficacious in controlling major Lepidopteran maize pests: laboratory resistance selection versus field reality
作者: Wen, Zhimou ; Conville, Jared ; Matthews, Phillip ; Hootman, Travis ; Himes, Jo ; Wong, Sarah ; Huang, Fangneng ; Ni, Xinzhi ; Chen, Jeng Shong ; Bramlett, Matthew
MIR162, a maize event that expresses Vip3Aa20 (Vip3A) approved for commercial cultivation around 2010, has been excellent for control of major Lepidopteran pests. However, development of fall armyworm (FAW) resistance to Vip3A is a serious concern. Resistant colonies selected in the laboratory can serve as valuable tools not only for better understanding of Vip3A's mode of action (MOA) and mechanism of resistance (MOR) but also for screening novel leads of new MOA that will help control FAW in case resistance to Vip3A in the field becomes a reality. We selected a Vip3A-resistant FAW strain, FAWVip3AR, by subjecting a FAW founder population containing field genetics to Vip3A exposure. FAWVip3AR had >9800-fold resistance to Vip3A by diet surface overlay bioassays and resistance was stable. Feeding bioassays using detached leaf tissues or whole plants indicated that FAWVip3AR larvae readily fed and completed the full life cycle on Vip3A-expressing MIR162 maize plants and leaf tissues that killed 100% of susceptible larvae. Yet, FAWVip3AR faced at least two challenges. First, FAWVip3AR suffered an apparent disadvantage (incomplete resistance) when feeding on MIR162 in comparison to FAWVip3AR feeding on Vip3A-free isoline AX5707 maize; and second, FAWVip3AR showed a fitness costs in comparison to a Vip3A-susceptible strain when both fed on AX5707. We also demonstrated that, >10 years after commercialization, MIR162 and Vip3A remain highly efficacious against field populations of three major Lepidopteran pests from different geographic locations and FAW strains resistant to other Bacillus thuringiensis (Bt) toxins that are currently on the market.
2023-03-20·ACS Agricultural Science & Technology
Influence of Nozzle Type and Wind Speed on Deposition and Interception of Pesticide Spray Drift: A Case Study with Atrazine
作者: Szarka, Arpad Z. ; Perkins, Daniel ; Golus, Jeff ; Vukoja, Barbara ; Schroeder, Kasey ; Henry, Jerri Lynn ; Brain, Richard
A wind tunnel study was conducted to compare spray drift deposition and interception profiles across ASABE (American Society of Agricultural and Biol. Engineers) coarse, very coarse, and extremely coarse drop size distribution (DSD) categories as a function of wind speed. AAtrex 4L (atrazine) was used as the spray solution; disk (deposition) and rod (interception) sampling devices were deployed at multiple distances and subject to spray drift at multiple wind speeds. Drift deposition was equivalent for the coarse spray delivered at 10 mph [16.1 km/h] and the extremely coarse spray delivered at 15 mph [24.1 km/h]. Intercepted (airborne) drift was indistinguishable between the coarse spray delivered at 10 mph [6.2 km/h] and very coarse spray delivered at 15 mph [6.2 km/h], and very coarse spray delivered at 10 mph [6.2 km/h] and extremely coarse spray delivered at 15 mph [24.1 km/h]. Regulatory decisions regarding potential buffer/setback mitigations would benefit from leveraging results regarding nozzle and wind speed relationships reported in this study and others to better utilize available exptl. drift data (e.g., field studies/bioassays) generated with a single nozzle but at wind speeds exceeding the label specification.
A site-specific indicator of nitrogen loads into surface waters from conventional and conservation agriculture practices: Bayesian network model
作者: Radomyski, Artur ; Ashauer, Roman
Agriculture is one of the main sources of diffuse pollution, such as fertilisers, plant protection products, solid particles or pathogens. The short- and long-term impact of agriculture on surface water quality is often driven by on-farm decisions as to what practices are used to manage weeds. Farming practices can affect numerous processes such as surface runoff and soil erosion which mediate release and transport of potential pollutants to edge-of-field water courses. Excessive nitrogen emissions are an ongoing problem of many farmlands, leading to pollution of surface water bodies and causing adverse outcomes such as eutrophication, resulting in deteriorating water quality. We developed a Bayesian Network (BN) model to predict nitrogen load into surface waters at the farm level using site specific characteristics such as landscape, soil, cropping system and, also, to compare different conventional and conservation agriculture practices. The BN was built from well-established and accepted models i.e., surface runoff by water is based on the Curve Number method (CN), the soil erosion rate is calculated with the Universal Soil Loss Equation (USLE), and nitrogen load is calculated based on a multilevel model, where the CN and the USLE outputs are used as inputs. All three sub-models produced satisfactory spread around 1:1 line. A classification technique was applied to evaluate predicted nitrogen loads against the reference data from the US EPA STEPL model with respect to nitrogen load threshold values. Out of all the data simulated with the BN 83 % agree with the reference model for the 20 kg/(ha x yr) nitrogen load threshold, and 97 % agree when the threshold is set to the middle of the prediction range, 100 kg/(ha x yr). The modeling exercise was performed on two pedo-climatic scenarios differing in their potential to generate surface runoff water and by considering the effect of combining three farming practices and two generic groups of crops on emitted nitrogen loads expressed as the Gray Water Footprint (GWF). Sensitivity anal. shows high importance of weather inputs for surface runoff, and topog. information for soil erosion, whereas agricultural treatments were ranked as less important. Under variable precipitation no-till practice would result in reducing emissions of water, soil and nitrogen compared to conventional farming. The results indicate that no-till practice would reduce nitrogen loads on sites with varying risk of runoff, and that a combination of no-till and small grain crops provides the best benefit in reducing nitrogen emissions. We demonstrate that a Baye′s net is a useful, flexible tool for data and knowledge assimilation and a practical approach to test and compare effects of various agricultural interventions on pollutant emissions from a farming system.
BASEL, Switzerland--(BUSINESS WIRE)-- Syngenta Group has withdrawn its STAR Market IPO application and will immediately apply for a public listing on the main board at the Shanghai Stock Exchange.
The decision was made after China fully rolled out its registration-based share issuance scheme across the country in February – a move that will further improve China’s capital market and clearly define the roles of different boards. Now that the main board of the Shanghai Stock Exchange is meant mainly to support large-scale companies with mature business models and stable earnings performance (blue chips which are good representatives of their respective industries), we believe Syngenta Group, as a leading global agricultural technology company, fits better on the main board of Shanghai Stock Exchange, under its latest registration-based IPO scheme. This main board listing will enable Syngenta Group to access more diversified investors and will be conducive for the company’s long-term value.
About Syngenta Group
Syngenta Group is one of the world’s biggest agricultural technology companies, with roots going back more than 250 years. With more than 57,000 employees, operating in more than 100 countries, the company strives to transform agriculture with science-driven, technological innovations to deliver high productivity and high-quality food while fighting climate change and restore nature. Syngenta Group is working with farmers to enable Regenerative Agriculture - an outcome-based food production system that nurtures and restores soil health, protects the climate and water resources and biodiversity, and enhances farms' productivity and profitability. Syngenta Group, which is registered in Shanghai, China, and has its management headquarters in Switzerland, draws strength from its four business units: Syngenta Crop Protection, headquartered in Switzerland; Syngenta Seeds, headquartered in the United States; ADAMA®, headquartered in Israel; and Syngenta Group China. Together, these businesses provide industry-leading ways to serve customers around the world.
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