AI can empower agriculture for global food security: challenges and prospects in developing nations

A Ahmad, AXW Liew, F Venturini… - Frontiers in Artificial …, 2024 - frontiersin.org
Food and nutrition are a steadfast essential to all living organisms. With specific reference to
humans, the sufficient and efficient supply of food is a challenge as the world population …

TPE-CatBoost: An adaptive model for soil moisture spatial estimation in the main maize-producing areas of China with multiple environment covariates

J Yu, W Zheng, L Xu, F Meng, J Li, L Zhangzhong - Journal of Hydrology, 2022 - Elsevier
Maize is one of the major crops in China. The soil water content (SWC) in the root zone of
maize is a critical indicator that guides agricultural production decisions and can affect …

[HTML][HTML] A multihead LSTM technique for prognostic prediction of soil moisture

P Datta, SA Faroughi - Geoderma, 2023 - Elsevier
Prognostic prediction of soil moisture is a critical step in various fields such as geotechnical
engineering, agriculture, geology, hydrology, and climatology. For example, in agricultural …

[HTML][HTML] Comparison of Machine Learning Methods for Predicting Soil Total Nitrogen Content Using Landsat-8, Sentinel-1, and Sentinel-2 Images

Q Zhang, M Liu, Y Zhang, D Mao, F Li, F Wu, J Song… - Remote Sensing, 2023 - mdpi.com
Soil total nitrogen (STN) is a crucial component of the ecosystem's nitrogen pool, and
accurate prediction of STN content is essential for understanding global nitrogen cycling …

[HTML][HTML] Comparison of random forest and kriging models for soil organic carbon mapping in the Himalayan Region of Kashmir

I Farooq, SA Bangroo, O Bashir, TI Shah, AA Malik… - Land, 2022 - mdpi.com
The knowledge about the spatial distribution of soil organic carbon stock (SOCS) helps in
sustainable land-use management and ecosystem functioning. No such study has been …

[HTML][HTML] Comparative analysis of machine and deep learning models for soil properties prediction from hyperspectral visual band

D Datta, M Paul, M Murshed, SW Teng, L Schmidtke - Environments, 2023 - mdpi.com
Estimating various properties of soil, including moisture, carbon, and nitrogen, is crucial for
studying their correlation with plant health and food production. However, conventional …

National-scale spatial prediction of soil organic carbon and total nitrogen using long-term optical and microwave satellite observations in Google Earth Engine

T Zhou, W Lv, Y Geng, S Xiao, J Chen, X Xu… - … and Electronics in …, 2023 - Elsevier
Modeling accurate and detailed soil spatial information is essential for environmental
modeling, precision soil management and decision-making. In this study, we integrated long …

Mapping the maximum peat thickness of cultivated organic soils in the southwest plain of Montreal

R Deragon, DD Saurette, B Heung… - Canadian Journal of …, 2023 - cdnsciencepub.com
Large organic deposits in the southwestern plain of Montreal have been converted to
agricultural land for vegetable production. In addition to the variable depth of the organic …

Evaluating different machine learning algorithms for snow water equivalent prediction

M Vafakhah, A Nasiri Khiavi, S Janizadeh… - Earth Science …, 2022 - Springer
The purpose of current study is to predict Snow Water Equivalent (SWE) in Sohrevard
watershed, Iran, using different machine learning algorithms such as Bayesian Artificial …

Improving spatial resolution of satellite soil water index (SWI) maps under clear-sky conditions using a machine learning approach

S Fathololoumi, MK Firozjaei, A Biswas - Journal of Hydrology, 2022 - Elsevier
One of the limitations of daily Soil Water Index (SWI) products obtained from satellite
imagery is the low spatial resolution, limiting their precise applications. The purpose of this …