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 rearing silkworm (Bombyx mori L.) larvae to produce silk in form cocoons, is practice that rarely used remote sensing techniques but could benefit from them. The aim this work was investigate possibility using satellite imaging order monitor leaf harvesting mulberry (Morus alba plants cultivated feeding silkworms; additionally, quantitative parameters on cocoon production were related analyses vegetation indices. Adopting PlanetScope images, four M. fields monitored beginning season until its end 2020 and 2021. results our showed a decrease multispectral indices plots due correlated with different cocoons spun by larvae; particular, Normalized Difference Vegetation Index (NDVI) Soil Adjusted (SAVI) had high correlations (R2 values up 0.56, p < 0.05). These led us conclusion agriculture can improve sericultural practice, offering interesting solutions estimating quantity produced through analysis fields.