Remote sensing imaging as a tool to support mulberry cultivation for silk production

In recent decades there has been an increasing use of remotely sensed data for precision agricultural purposes. Sericulture, the activity of rearing silkworm (Bombyx mori L.) larvae to produce silk in the form of cocoons, is an agricultural practice that has rarely used remote sensing techniques but...

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Detalhes bibliográficos
Autores: Giora, Domenico, Assirelli, Alberto, Cappellozza, Silvia, Sartori, Luigi, Saviane, Alessio, Marinello, Francesco, Martínez Casasnovas, José Antonio
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Recursos:Universitat de Lleida (UdL)
Repositorio:Repositori Obert UdL
OAI Identifier:oai:repositori.udl.cat:10459.1/84454
Acesso em linha:https://doi.org/10.3390/rs14215450
http://hdl.handle.net/10459.1/84454
Access Level:acceso abierto
Palavra-chave:Bombyx moriL
Cocoon
Morus albaL
Precision agriculture
Remote sensing
Satellite images
Sericicultura
Seda
Descrição
Resumo:In recent decades there has been an increasing use of remotely sensed data for precision agricultural purposes. Sericulture, the activity of rearing silkworm (Bombyx mori L.) larvae to produce silk in the form of cocoons, is an agricultural practice that has rarely used remote sensing techniques but that could benefit from them. The aim of this work was to investigate the possibility of using satellite imaging in order to monitor leaf harvesting in mulberry (Morus alba L.) plants cultivated for feeding silkworms; additionally, quantitative parameters on silk cocoon production were related to the analyses on vegetation indices. Adopting PlanetScope satellite images, four M. alba fields were monitored from the beginning of the silkworm rearing season until its end in 2020 and 2021. The results of our work showed that a decrease in the multispectral vegetation indices in the mulberry plots due to leaf harvesting was correlated with the different parameters of silk cocoons spun by silkworm larvae; in particular, a decrease in the Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) had high correlations with quantitative silk cocoon production parameters (R2 values up to 0.56, p < 0.05). These results led us to the conclusion that precision agriculture can improve sericultural practice, offering interesting solutions for estimating the quantity of produced silk cocoons through the remote analysis of mulberry fields.