A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction

M Rashid, BS Bari, Y Yusup, MA Kamaruddin… - IEEE …, 2021 - ieeexplore.ieee.org
An early and reliable estimation of crop yield is essential in quantitative and financial
evaluation at the field level for determining strategic plans in agricultural commodities for …

Forecasting yield by integrating agrarian factors and machine learning models: A survey

D Elavarasan, DR Vincent, V Sharma… - … and electronics in …, 2018 - Elsevier
The advancement in science and technology has led to a substantial amount of data from
various fields of agriculture to be incremented in the public domain. Hence a desideratum …

Crop yield prediction using deep reinforcement learning model for sustainable agrarian applications

D Elavarasan, PMD Vincent - IEEE access, 2020 - ieeexplore.ieee.org
Predicting crop yield based on the environmental, soil, water and crop parameters has been
a potential research topic. Deep-learning-based models are broadly used to extract …

Prediction of crop yield using phenological information extracted from remote sensing vegetation index

Z Ji, Y Pan, X Zhu, J Wang, Q Li - Sensors, 2021 - mdpi.com
Phenology is an indicator of crop growth conditions, and is correlated with crop yields. In this
study, a phenological approach based on a remote sensing vegetation index was explored …

[HTML][HTML] Combining UAV-based hyperspectral imagery and machine learning algorithms for soil moisture content monitoring

X Ge, J Wang, J Ding, X Cao, Z Zhang, J Liu, X Li - PeerJ, 2019 - peerj.com
Soil moisture content (SMC) is an important factor that affects agricultural development in
arid regions. Compared with the space-borne remote sensing system, the unmanned aerial …

What do we know about water scarcity in semi-arid zones? A global analysis and research trends

F Morante-Carballo, N Montalván-Burbano… - Water, 2022 - mdpi.com
Water supply is strategic for the development of society. The water distribution in nature
follows patterns linked to geographic and territorial issues. Climate fluctuations aggravate …

[HTML][HTML] Prediction of winter wheat yield and dry matter in North China Plain using machine learning algorithms for optimal water and nitrogen application

Y Wang, W Shi, T Wen - Agricultural Water Management, 2023 - Elsevier
Accurate prediction of crop yield and dry matter as well as optimized water and nitrogen
management can favor rational decision-making for farming systems. Combining high …

Soil moisture content retrieval from Landsat 8 data using ensemble learning

Y Zhang, S Liang, Z Zhu, H Ma, T He - ISPRS Journal of Photogrammetry …, 2022 - Elsevier
Although detailed spatial and temporal distribution of soil moisture is crucial for numerous
applications, current global soil moisture products generally have low spatial resolutions (25 …

Incorporating environmental variables into a MODIS-based crop yield estimation method for United States corn and soybeans through the use of a random forest …

T Sakamoto - ISPRS Journal of Photogrammetry and Remote …, 2020 - Elsevier
Satellite-based remote sensing is a powerful form of technology that can provide food
security policy makers with reliable information. This information allows them to estimate …

Combining optical, fluorescence, thermal satellite, and environmental data to predict county-level maize yield in China using machine learning approaches

L Zhang, Z Zhang, Y Luo, J Cao, F Tao - Remote Sensing, 2019 - mdpi.com
Maize is an extremely important grain crop, and the demand has increased sharply
throughout the world. China contributes nearly one-fifth of the total production alone with its …