Comparison of biological methods to control Aphis fabae Scopoli (Hemiptera: Aphididae) on kalanchoe crops in East Africa

Published online: 21 Dec 2020Aphids cause considerable damage to numerous crops all over the world and insecticides are the main means of controlling them, despite their detrimental impacts on human and environmental health. This study assessed the effectiveness of the parasitoid Aphidius colemani Viereck (Hymenoptera: Braconidae), a mixture of predatory ladybird beetles, Hippodamia variegata Goeze, Chilocorus calvus Chiccl, and Cheilomenes propinqua Mulsant (Coleoptera: Coccinellidae), and an entomopathogenic strain of Aspergillus flavus Link (Eurotiales: Trichocomaceae), collected locally in Tanzania, to control Aphis fabae Scopoli (Hemiptera: Aphididae). After assessing the predation and parasitism rates of these natural enemies at different aphid densities in laboratory experiments, their ability to control aphids on kalanchoe was assessed in a greenhouse experiment over two seasons. The largest number of A. fabae parasitized or consumed in the laboratory was found at a density of 160 aphids per predator, or parasitoid. At that density, an adult female of A. colemani parasitized 114 A. fabae per day, on average, and adults of C. calvus, H. variegata, and C. propinqua consumed 75, 72, and 85 aphids per day, respectively. A. flavus spores applied at 1 × 107 spores ml−1 reduced the aphid population by 7.9 and 12.6 times within 10 days in the first and second seasons of the greenhouse experiments, respectively, as opposed to 2.8 and 2.5 times by releasing a mixture of the ladybirds at a rate of 5 adults/m2, and by 3.3 and 9.5 times by releasing A. colemani at a rate of 2 adults/m2. This study confirmed the potential of these locally collected bio-control agents for controlling A. fabae. However, use of the isolated A. flavus strain was undermined by its production of aflatoxin. Further research is therefore required to tap into the potential of a non-toxic strain of A. flavus and/or other entomopathogenic fungi

Is machine learning efficient for mango yield estimation when used under heterogeneous field conditions?

International audienceIn the last decade, image analysis using machine learning algorithms proved its potential for the detection and counting of plant organs. Numerous studies provided fruit tree yield estimates based on machine learning with high levels of efficiency. However, most of these studies were conducted under homogeneous conditions of fruit aspect. The aim of this study was to develop an efficient machine learning method for ripe mango fruit detection from RGB images and to test it under heterogeneous field conditions for tree yield estimation in Senegal. The algorithm consisted in a k-nearest neighbours classification based on colour and texture features followed by a post-treatment based on shape indices. The F1 score, which accounts for both precision and recall performances, reached 0.73 for a set of 42 images of ‘Kent’ trees in homogeneous conditions. When performed on a second set of 128 images representing the actual heterogeneity in tree structure (height, canopy volume) and cultivars (‘Kent’, ‘Keitt’ and ‘Boucodiékhal’) found in the Niayes region of Senegal, the F1 score fell to 0.48. This decrease resulted from the heterogeneous field conditions in terms of fruit size, fruit colour and light exposure caused by different tree structures among cultivars. Despite the algorithm was less efficient under these conditions, significant linear relationships were evidenced between the number of detected fruits and the actual number of fruits per tree for each cultivar (‘Kent’: R2=0.92, ‘Keitt’: R2=0.93, and ‘Boucodiékhal’: R2=0.90). These models were cross-validated and reached a relative RMSE of 14%. Those results offer new opportunities to accurately and rapidly estimate mango yield and to further identify the parameters that drive its variability at the tree and orchard scales

Agroecological transformation for sustainable food systems : Insight on France-CGIAR research

This 26th dossier d’Agropolis is devoted to research and partnerships in agroecology. The French Commission for International Agricultural Research (CRAI) and Agropolis International, on behalf of CIRAD, INRAE and IRD and in partnership with CGIAR, has produced this new issue in the ‘Les dossiers d’Agropolis international’ series devoted to agroecology. This publication has been produced within the framework of the Action Plan signed by CGIAR and the French government on February 4th 2021 to strengthen French collaboration with CGIAR, where agroecology is highlighted as one of the three key priorities (alongside climate change, nutrition and food systems)