A systematic literature review on crop yield prediction with deep learning and remote sensing

P Muruganantham, S Wibowo, S Grandhi, NH Samrat… - Remote Sensing, 2022 - mdpi.com
Deep learning has emerged as a potential tool for crop yield prediction, allowing the model
to automatically extract features and learn from the datasets. Meanwhile, smart farming …

Do crop sensors promote improved nitrogen management in grain crops?

AF Colaço, RGV Bramley - Field Crops Research, 2018 - Elsevier
Crop sensing technologies to aid nitrogen management in grain crops have been the focus
of an important element of Precision/Digital Agriculture research. We review sensor-based …

Improving estimation of summer maize nitrogen status with red edge-based spectral vegetation indices

F Li, Y Miao, G Feng, F Yuan, S Yue, X Gao, Y Liu… - Field Crops …, 2014 - Elsevier
In recent decades, many spectral indices have been proposed to estimate crop nitrogen (N)
status parameters. However, most of the indices based on red radiation lose their sensitivity …

Hyperspectral canopy sensing of paddy rice aboveground biomass at different growth stages

ML Gnyp, Y Miao, F Yuan, SL Ustin, K Yu, Y Yao… - Field Crops …, 2014 - Elsevier
Abstract Normalized Difference Vegetation Index and Ratio Vegetation Index obtained with
the fixed band GreenSeeker active multispectral canopy sensor (GS-NDVI and GS-RVI) …

Improving nitrogen use efficiency and reducing nitrogen surplus through best fertilizer nitrogen management in cereal production: The case of India and China

TB Sapkota, R Takele - Advances in Agronomy, 2023 - Elsevier
China and India are the two top consumers of fertilizer nitrogen (N) in the world not only to
provide food security to 36% of the global population living in the two countries but also due …

Advances in the estimations and applications of critical nitrogen dilution curve and nitrogen nutrition index of major cereal crops. A review

X Li, ST Ata-UI-Karim, Y Li, F Yuan, Y Miao… - … and Electronics in …, 2022 - Elsevier
Nitrogen (N) is one of the decisive elements for plant growth, crop biomass accumulation,
and yield formation of cereal crops. However, managing N in crop production and …

Multitemporal crop surface models: accurate plant height measurement and biomass estimation with terrestrial laser scanning in paddy rice

N Tilly, D Hoffmeister, Q Cao, S Huang… - Journal of Applied …, 2014 - spiedigitallibrary.org
Appropriate field management requires methods of measuring plant height with high
precision, accuracy, and resolution. Studies show that terrestrial laser scanning (TLS) is …

Non-destructive estimation of rice plant nitrogen status with Crop Circle multispectral active canopy sensor

Q Cao, Y Miao, H Wang, S Huang, S Cheng… - Field Crops …, 2013 - Elsevier
Crop Circle is an active multispectral canopy sensor developed to support precision crop
management. The Crop Circle ACS-470 model is user configurable, with a choice of six …

Predicting rice grain yield based on dynamic changes in vegetation indexes during early to mid-growth stages

K Zhang, X Ge, P Shen, W Li, X Liu, Q Cao, Y Zhu… - Remote sensing, 2019 - mdpi.com
Predicting the grain yield during early to mid-growth stages is important for initial diagnosis
of rice and quantitative regulation of topdressing. In this study, we conducted four …

Machine learning-based in-season nitrogen status diagnosis and side-dress nitrogen recommendation for corn

X Wang, Y Miao, R Dong, H Zha, T **a, Z Chen… - European Journal of …, 2021 - Elsevier
Reliable and efficient in-season nitrogen (N) status diagnosis and recommendation methods
are crucially important for the success of crop precision N management (PNM). The …