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Abstract

Rachiplusia nu (Lepidoptera: Noctuidae) is the main soybean plague in Argentina. The main strategy employed to control this pest is chemical control, applying different chemical groups regardless of their harmful effects on the environment and human health. Different biological products using entomopathogenic fungi have been developed and are commercially available to control different insect pests worldwide. The objective of this work was to develop and apply, under field conditions, different fungal formulations using entomopathogenic fungi to control R. nu larvae. The mortality percentages in bioassays of R. nu larvae treated with different colonies of fungal entomopathogens ranged between 86.6 ± 8.4% for Beauveria bassiana (LPSc 1098) and 56.6 ± 4.2% for Metarhizium anisopliae (LPSc 907). Under laboratory conditions using fungal formulations of B. bassiana, the formulation 4 (LPSc 1086) exhibited the highest mortality percentage (100%), followed by formulation 5 (LPSc 1098), 97 ± 1.3%. Under field conditions, larval mortalities were 82.4 ± 5.56% for formulation F4 and 61.8 ± 7.5% for formulation F5. The results obtained in this work indicate that although a greater number of tests under field conditions with the fungal formulation F4 are necessary, the results obtained in this work allow speculating that it is possible to use this fungal formulation under field conditions to control R. nu.
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Authors and Affiliations

Matías Abalo
1
ORCID: ORCID
Ana Clara Scorsetti
1
ORCID: ORCID
María Florencia Vianna
1
ORCID: ORCID
María Leticia Russo
1
ORCID: ORCID
Juan Manuel De Abajo
1
ORCID: ORCID
Sebastián Alberto Pelizza
1
ORCID: ORCID

  1. Instituto de Botánica Carlos Spegazzini, Facultad de Ciencias Naturales y Museo, Universidad Nacional de La Plata, Argentina
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Abstract

The world population is projected to reach 9.8 billion in 2050, and 11.2 billion in 2100 (United Nations) and people will need food, and decrease the farming land. Thus, the importance of Internet of Things (IoT) and Computer Science (CS) in plant disease management are increasing now-a-days. Mobile apps, remote sensing, spectral signature analysis, artificial neural networks (ANN), and deep learning monitors are commonly used in plant disease and pest management. IoT improves crop yield by fostering new farming methods along with the improvement of monitoring and management through cloud computing. In the quest for effective plant disease control, the future lies in cutting-edge technologies. The integration of IoT, artificial intelligence, and data analytics revolutionizes monitoring and diagnosis, enabling timely and precise interventions. Cloud computing facilitates real-time data sharing and analysis empower farmers to combat diseases with unprecedented efficiency. By harnessing these innovations, agriculture can embrace sustainable practices and safeguard crop health, ensuring a bountiful and secure future for the global food supply.
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Authors and Affiliations

Suborna Rani
1
Kallol Das
2
ORCID: ORCID
F.M. Aminuzzaman
3
ORCID: ORCID
Benjamin Yaw Ayim
4
ORCID: ORCID
Natasza Borodynko-Filas
5
ORCID: ORCID

  1. Faculty of Computer Science and Engineering, Patuakhali Science and Technology University, Patuakhali, Bangladesh
  2. College of Agriculture and Life Sciences, Kyungpook National University, Daegu, Republic of Korea
  3. Department of Plant Pathology, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh
  4. Ministry of Food and Agriculture, Plant Protection and Regulatory Services Directorate, Ashanti, Ghana
  5. Plant Disease Clinic and Bank of Pathogens, Institute of Plant Protection – National Research Institute, Poznan, Poland

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