APA (7th ed.) Citation

Jewan, S., Gautam, D., Sparkes, D., Singh, A., Billa, L., Cogato, A., . . . Pagay, V. (2024). Integrating Hyperspectral, Thermal, and Ground Data with Machine Learning Algorithms Enhances the Prediction of Grapevine Yield and Berry Composition. Remote sensing (Basel, Switzerland), 16(23), 4539. https://doi.org/10.3390/rs16234539

Chicago Style (17th ed.) Citation

Jewan, Shaikh, Deepak Gautam, Debbie Sparkes, Ajit Singh, Lawal Billa, Alessia Cogato, Erik Murchie, and Vinay Pagay. "Integrating Hyperspectral, Thermal, and Ground Data with Machine Learning Algorithms Enhances the Prediction of Grapevine Yield and Berry Composition." Remote Sensing (Basel, Switzerland) 16, no. 23 (2024): 4539. https://doi.org/10.3390/rs16234539.

MLA (9th ed.) Citation

Jewan, Shaikh, et al. "Integrating Hyperspectral, Thermal, and Ground Data with Machine Learning Algorithms Enhances the Prediction of Grapevine Yield and Berry Composition." Remote Sensing (Basel, Switzerland), vol. 16, no. 23, 2024, p. 4539, https://doi.org/10.3390/rs16234539.