Nitrogen monitoring and inversion algorithms of fruit trees based on spectral remote sensing: a deep review

R Xi, Y Gu, X Zhang, Z Ren - Frontiers in Plant Science, 2024 - frontiersin.org
Nitrogen, as one of the important elements affecting the growth and development of fruit
trees, leads to slowed protein synthesis and reduced photosynthesis, resulting in yellowing …

Improving UAV hyperspectral monitoring accuracy of summer maize soil moisture content with an ensemble learning model fusing crop physiological spectral …

H Liu, J Chen, Y Xiang, H Geng, X Yang, N Yang… - European Journal of …, 2024 - Elsevier
Soil moisture content (SMC) acquisition is vital for crop stress diagnosis and precision
irrigation. However, UAV remote sensing-based SMC monitoring usually suffers from low …

Inversion of Leaf Water Content of Cinnamomum camphora Based on Preferred Spectral Index and Machine Learning Algorithm

B Yang, H Zhang, X Lu, H Wan, Y Zhang, J Zhang… - Forests, 2023 - mdpi.com
Plant leaf water content significantly influences photosynthetic efficiency and crop yield. Leaf
water content (LWC) and equivalent water thickness (EWT) are indicators that reflect the …

An improved digital soil mapping approach to predict total N by combining machine learning algorithms and open environmental data

A Auzzas, GF Capra, AD Jani, A Ganga - Modeling Earth Systems and …, 2024 - Springer
Abstract Digital Soil Mapping (DSM) is fundamental for soil monitoring, as it is limited and
strategic for human activities. The availability of high temporal and spatial resolution data …

[HTML][HTML] Performance of Machine Learning Models in Predicting Common Bean (Phaseolus vulgaris L.) Crop Nitrogen Using NIR Spectroscopy

MS Tavares, CAAC Silva, JR Regazzo, EJS Sardinha… - Agronomy, 2024 - mdpi.com
Beans are the main direct source of protein consumed by humans in the world and their
productivity is directly linked to nitrogen. The short crop cycle imposes the need for fast …

Informing the prediction of forage quality of Mediterranean grasslands using hyperspectral reflectance: Concentration vs content, phenology, and generalisation of …

J Fernández-Habas, Ó Perez-Priego… - Field Crops …, 2025 - Elsevier
Context Remote sensing has shown potential to provide accurate and real-time information
on grassland forage quality, crucial for the management of livestock systems. However …

Hyperspectral Estimation of Chlorophyll Content in Grape Leaves Based on Fractional-Order Differentiation and Random Forest Algorithm

Y Li, X Xu, W Wu, Y Zhu, G Yang, X Yang, Y Meng… - Remote Sensing, 2024 - mdpi.com
Chlorophyll, as a key component of crop leaves for photosynthesis, is one significant
indicator for evaluating the photosynthetic efficiency and developmental status of crops …

Estimation of photosynthetic parameters from hyperspectral images using optimal deep learning architecture

X Deng, Z Zhang, X Hu, J Li, S Li, C Su, S Du… - … and Electronics in …, 2024 - Elsevier
The maximum carboxylation rate (V cmax) and maximum electron transport rate (J max) of
leaves are crucial for comprehending carbon cycling in farmland. Nevertheless, estimating …

Non-destructive assessment of cannabis quality during drying process using hyperspectral imaging and machine learning

HI Yoon, SH Lee, D Ryu, H Choi, SH Park… - Frontiers in Plant …, 2024 - frontiersin.org
Cannabis sativa L. is an industrially valuable plant known for its cannabinoids, such as
cannabidiol (CBD) and Δ9-tetrahydrocannabinol (THC), renowned for its therapeutic and …

[HTML][HTML] Effects of Variety and Growth Stage on UAV Multispectral Estimation of Plant Nitrogen Content of Winter Wheat

M Shu, Z Wang, W Guo, H Qiao, Y Fu, Y Guo, L Wang… - Agriculture, 2024 - mdpi.com
The accurate estimation of nitrogen content in crop plants is the basis of precise nitrogen
fertilizer management. Unmanned aerial vehicle (UAV) imaging technology has been widely …