Assessing the Presence of Pithomyces chartarum in Pastureland Using IoT Sensors and Remote Sensing: The Case Study of Terceira Island (Azores, Portugal)

Author:

Ávila Mariana12ORCID,Pinelo João1ORCID,Casas Enrique2ORCID,Capinha César34,Pabst Rebecca5ORCID,Szczesniak Iga1,Domingues Elizabeth6,Pinto Carlos7ORCID,Santos Valentina8,Gil Artur9ORCID,Arbelo Manuel2ORCID

Affiliation:

1. Atlantic International Research Centre, 9700 Angra do Heroísmo, Portugal

2. Departamento de Física, Universidad de La Laguna, 38200 San Cristóbal de La Laguna, Spain

3. Centro de Estudos Geográficos, Instituto de Geografia e Ordenamento do Território da Universidade de Lisboa, Universidade de Lisboa, 1600 Lisbon, Portugal

4. Laboratório Associado Terra, 1349 Lisbon, Portugal

5. Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, 1349 Lisbon, Portugal

6. UNICOL-Cooperativa Agrícola, C.R.L., 9700 Angra do Heroísmo, Portugal

7. Faculdade de Ciências Agrárias e do Ambiente (FCAA), Universidade dos Açores, 9700 Angra do Heroísmo, Portugal

8. Laboratório Regional de Veterinária, 9700 Angra do Heroísmo, Portugal

9. Instituto de Investigação em Vulcanologia e Avaliação de Riscos (IVAR), Universidade dos Açores, 9500 Ponta Delgada, Portugal

Abstract

Spores from the fungus Pithomyces chartarum are commonly found on Azorean pastures. When consumed by cattle along with the grass, these spores cause health issues in the cattle, resulting in animal suffering and financial losses. For approximately two years, we monitored meteorological parameters using weather stations and collected and analyzed grass samples in a laboratory to control for the presence of spores. The data confirmed a connection between meteorology and sporulation, enabling the prediction of sporulation risk. To detect the presence of spores in pastures rather than predict it, we employed field spectrometry and Sentinel-2 reflectance data to measure the spectral signatures of grass while controlling for spores. Our findings indicate that meteorological variables from the past 90 days can be used to predict sporulation, which can enhance the accuracy of a web-based alert system used by farmers to manage the risk. We did not detect significant differences in spectral signatures between grass with and without spores. These studies contribute to a deeper understanding of P. chartarum sporulation and provide actionable information for managing cattle, ultimately improving animal welfare and reducing financial losses.

Funder

PO AÇORES 2020 program

Publisher

MDPI AG

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