scholarly journals Challenges for integrated pest management of Dasineura brassicae in oilseed rape

2021 ◽  
Vol 15 (5) ◽  
pp. 645-656
Author(s):  
Johannes Hausmann

AbstractThe use of insecticides in flowering oilseed rape (Brassica napus L.) against pest insects such as the brassica pod midge (Dasineura brassicae W.) often conflicts with the protection of pollinating and beneficial insects. Dasineura brassicae is a major pest insect in European oilseed rape production. However, a comprehensive and sustainable pest control strategy within the framework of integrated pest management (IPM) does not exist, and little research on the insect has been published during the past two decades. This paper reviews the existing knowledge about D. brassicae along its life cycle and is intended to form the basis for further research activities on pod-damaging pest insects in oilseed rape. Important knowledge gaps are identified, regarding the significance of natural enemies, diapause induction, and predictions on damage potential, based on initial pest insect population. The short lifespan of the adults is particularly challenging in praxis. The implementation of IPM for D. brassicae is discussed on the basis of the four IPM steps (set an economic threshold, establish pest monitoring, preventive measures, and direct control measures) and remaining hurdles, as well as potential solutions for a better IPM, are identified. For D. brassicae, there is no science-based economic threshold and no applicable monitoring methods for farmers, which hinders a field-specific damage forecast and the precise timing of insecticide applications. Research into improved monitoring (e.g. selective attractants, real-time monitoring using remote-sensing technologies) appears to be a promising step towards an integrated pest management of D. brassicae.

2003 ◽  
Vol 95 (2-3) ◽  
pp. 509-521 ◽  
Author(s):  
Andrew W Ferguson ◽  
Zdisław Klukowski ◽  
Barbara Walczak ◽  
Suzanne J Clark ◽  
Moira A Mugglestone ◽  
...  

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Yong He ◽  
Hong Zeng ◽  
Yangyang Fan ◽  
Shuaisheng Ji ◽  
Jianjian Wu

In this paper, we proposed an approach to detect oilseed rape pests based on deep learning, which improves the mean average precision (mAP) to 77.14%; the result increased by 9.7% with the original model. We adopt this model to mobile platform to let every farmer able to use this program, which will diagnose pests in real time and provide suggestions on pest controlling. We designed an oilseed rape pest imaging database with 12 typical oilseed rape pests and compared the performance of five models, SSD w/Inception is chosen as the optimal model. Moreover, for the purpose of the high mAP, we have used data augmentation (DA) and added a dropout layer. The experiments are performed on the Android application we developed, and the result shows that our approach surpasses the original model obviously and is helpful for integrated pest management. This application has improved environmental adaptability, response speed, and accuracy by contrast with the past works and has the advantage of low cost and simple operation, which are suitable for the pest monitoring mission of drones and Internet of Things (IoT).


2020 ◽  
Vol 27 (1) ◽  
pp. 107327482092254
Author(s):  
Christopher J. Whelan ◽  
Jessica J. Cunningham

The “war on cancer” began over 40 years ago with the signing of the National Cancer Act of 1971. Currently, complete eradication has proven possible in early stage premetastatic disease with increasingly successful early detection and surgery protocols; however, late stage metastatic disease remains invariably fatal. One of the main causes of treatment failure in metastatic disease is the ability of cancer cells to evolve resistance to currently available therapies. Evolution of resistance to control measures is a universal problem. While it may seem that the mechanisms of resistance employed by cancer cells are impossible to control, we show that many of the resistance mechanisms are mirrored in agricultural pests. In this way, we argue that measures developed in the agricultural industry to slow or prevent pesticide resistance could be adopted in clinical cancer biology to do the same. The agriculture industry recognized the problem of pesticide resistance and responded by developing and enforcing guidelines on resistance management and prevention. These guidelines, known as integrated pest management (IPM), do not encourage eradication of pests but instead strive to maintain pests, even with the presence of resistant strains, at a level that does not cause economic damage to the crops. Integrated pest management inspired management of metastatic cancer could result in the slowing or curtailing of widespread resistance to treatment, reducing overall drug usage, and increasing the survival and quality of life of patients with cancer. Using IPM principles as a foundation and shifting the goal of treatment of metastatic disease to long-term management will require close monitoring of evolving tumor populations, judicious application of currently available therapies, and development of new criteria of success.


2011 ◽  
Vol 101 (6) ◽  
pp. 640-643 ◽  
Author(s):  
David H. Gent ◽  
Erick De Wolf ◽  
Sarah J. Pethybridge

Rational management of plant diseases, both economically and environmentally, involves assessing risks and the costs associated with both correct and incorrect tactical management decisions to determine when control measures are warranted. Decision support systems can help to inform users of plant disease risk and thus assist in accurately targeting events critical for management. However, in many instances adoption of these systems for use in routine disease management has been perceived as slow. The under-utilization of some decision support systems is likely due to both technical and perception constraints that have not been addressed adequately during development and implementation phases. Growers' perceptions of risk and their aversion to these perceived risks can be reasons for the “slow” uptake of decision support systems and, more broadly, integrated pest management (IPM). Decision theory provides some tools that may assist in quantifying and incorporating subjective and/or measured probabilities of disease occurrence or crop loss into decision support systems. Incorporation of subjective probabilities into IPM recommendations may be one means to reduce grower uncertainty and improve trust of these systems because management recommendations could be explicitly informed by growers' perceptions of risk and economic utility. Ultimately though, we suggest that an appropriate measure of the value and impact of decision support systems is grower education that enables more skillful and informed management decisions independent of consultation of the support tool outputs.


Author(s):  
Marika Mänd ◽  
Ingrid H. Williams ◽  
Eneli Viik ◽  
Reet Karise

2017 ◽  
Vol 46 (5) ◽  
pp. 1041-1050 ◽  
Author(s):  
Anna K Wallingford ◽  
Dong H Cha ◽  
Charles E Linn ◽  
Michael S Wolfin ◽  
Gregory M Loeb

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