Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery
Summary
Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery is a scholarly article[1].
Key Facts
Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery. Retrieved May 24, 2026, from https://4ort.xyz/entity/predicting-grain-yield-in-rice-using-multi-temporal-vegetation-indices-from-uav-based-multispectral-and-digital-imagery
MLA“Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/predicting-grain-yield-in-rice-using-multi-temporal-vegetation-indices-from-uav-based-multispectral-and-digital-imagery.
BibTeX@misc{4ortxyz_predicting-grain-yield-in-rice-using-multi-temporal-vegetation-indices-from-uav-based-multispectral-and-digital-imagery_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery}}, year = {2026}, url = {https://4ort.xyz/entity/predicting-grain-yield-in-rice-using-multi-temporal-vegetation-indices-from-uav-based-multispectral-and-digital-imagery}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery — https://4ort.xyz/entity/predicting-grain-yield-in-rice-using-multi-temporal-vegetation-indices-from-uav-based-multispectral-and-digital-imagery (retrieved 2026-05-24)