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7 results for “pest damage”
Data from: Extrapolating potential crop damage by insect pests based on land use data: examining inter-regional generality in agricultural landscapes_210907
<p>DamagePrediction_data_2021_210907 Data from: Extrapolating potential crop damage by insect pests based on land use data: examining inter-regional generality in agricultural landscapes</p>
Data from: High effectiveness of tailored flower strips in reducing pests and crop plant damage
Providing key resources to animals may enhance both their biodiversity and the ecosystem services they provide. We examined the performance of annual flower strips targeted at the promotion of natural pest control in winter wheat. Flower strips were experimentally sown along 10 winter wheat fields across a gradient of landscape complexity (i.e. proportion non-crop area within 750 m around focal fields) and compared with 15 fields with wheat control strips. We found strong reductions in cereal leaf beetle (CLB) density (larvae: 40%; adults of the second generation: 53%) and plant damage caused by CLB (61%) in fields with flower strips compared with control fields. Natural enemies of CLB were strongly increased in flower strips and in part also in adjacent wheat fields. Flower strip effects on natural enemies, pests and crop damage were largely independent of landscape complexity (8–75% non-crop area). Our study demonstrates a high effectiveness of annual flower strips in promoting pest control, reducing CLB pest levels below the economic threshold. Hence, the studied flower strip offers a viable alternative to insecticides. This highlights the high potential of tailored agri-environment schemes to contribute to ecological intensification and may encourage more farmers to adopt such schemes.
In 2017, Plantix, a free smartphone app that helps identify plant damage, was introduced to the Indian state of Andhra Pradesh, with an extension partner. Plantix was created by Progressive Environmental and Agricultural Technologies (PEAT), a German startup. Two PEAT cofounders, Charlotte Schuman (second from the right) and Alex Kennepohl (center, with eyeglasses), confer about the smartphone app with students from Angrau University. Farmers and gardeners can transmit their plant images to Plantix, which uses deep learning and computer vision to help identify diseases and pests. The smartphone app offers symptom descriptions, treatment recommendations, and potential preventive actions. Photographs: Courtesy of PEAT GmbH. in Deep learning brings speed, accuracy to the life sciences.
In 2017, Plantix, a free smartphone app that helps identify plant damage, was introduced to the Indian state of Andhra Pradesh, with an extension partner. Plantix was created by Progressive Environmental and Agricultural Technologies (PEAT), a German startup. Two PEAT cofounders, Charlotte Schuman (second from the right) and Alex Kennepohl (center, with eyeglasses), confer about the smartphone app with students from Angrau University. Farmers and gardeners can transmit their plant images to Plantix, which uses deep learning and computer vision to help identify diseases and pests. The smartphone app offers symptom descriptions, treatment recommendations, and potential preventive actions. Photographs: Courtesy of PEAT GmbH.
Data from: High effectiveness of tailored flower strips in reducing pests and crop plant damage
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Fig. 1 in Impacts of crop residue on damage by sugarcane pests during the tillering phase in Argentina
Fig. 1. Injury (proportion of damaged shoots) caused by Elasmopalpus lignosellus (a) and Pseudaletia unipuncta (b), for 2 harvest residue management schemes at 3 locations, 2011 to 2013.
Data from: Pest tradeoffs in technology: reduced damage by caterpillars in Bt cotton benefits aphids
The rapid adoption of genetically engineered (GE) plants that express insecticidal Cry proteins derived from Bacillus thuringiensis (Bt) has raised concerns about their potential impact on non-target organisms. This includes the possibility that non-target herbivores develop into pests. Although studies have now reported increased populations of non-target herbivores in Bt cotton, the underlying mechanisms are not fully understood. We propose that lack of herbivore-induced secondary metabolites in Bt cotton represents a mechanism that benefits non-target herbivores. We show that, because of effective suppression of Bt-sensitive lepidopteran herbivores, Bt cotton contains reduced levels of induced terpenoids. We also show that changes in the overall level of these defensive secondary metabolites are associated with improved performance of a Bt-insensitive herbivore, the cotton aphid, under glasshouse conditions. These effects, however, were not as clearly evident under field conditions as aphid populations were not correlated with the amount of terpenoids measured in the plants. Nevertheless, increased aphid numbers were visible in Bt cotton compared with non-Bt cotton on some sampling dates. Identification of this mechanism increases our understanding of how insect-resistant crops impact herbivore communities and helps underpin the sustainable use of GE varieties.
Data from: Pest tradeoffs in technology: reduced damage by caterpillars in Bt cotton benefits aphids
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