Artificial intelligence technology in the agricultural sector: A systematic literature review

E Elbasi, N Mostafa, Z AlArnaout, AI Zreikat… - IEEE …, 2022 - ieeexplore.ieee.org
Due to the increasing global population and the growing demand for food worldwide as well
as changes in weather conditions and the availability of water, artificial intelligence (AI) such …

Adoption of Unmanned Aerial Vehicle (UAV) imagery in agricultural management: A systematic literature review

MA Istiak, MMM Syeed, MS Hossain, MF Uddin… - Ecological …, 2023 - Elsevier
Precision agriculture and Smart farming have become the essential backbone for
sustainable agricultural production by leveraging cutting edge remote sensing and …

Automated wheat diseases classification framework using advanced machine learning technique

H Khan, IU Haq, M Munsif, Mustaqeem, SU Khan… - Agriculture, 2022 - mdpi.com
Around the world, agriculture is one of the important sectors of human life in terms of food,
business, and employment opportunities. In the farming field, wheat is the most farmed crop …

Drone image segmentation using machine and deep learning for map** raised bog vegetation communities

S Bhatnagar, L Gill, B Ghosh - Remote Sensing, 2020 - mdpi.com
The application of drones has recently revolutionised the map** of wetlands due to their
high spatial resolution and the flexibility in capturing images. In this study, the drone imagery …

Evaluation of water status of wheat genotypes to aid prediction of yield on sodic soils using UAV-thermal imaging and machine learning

S Das, J Christopher, A Apan, MR Choudhury… - Agricultural and Forest …, 2021 - Elsevier
Water stress limits wheat growth and the yield on rain-fed sodic soils. Appropriate selection
of traits and novel methods are required to forecast yield and to identify water stress tolerant …

UAV-Thermal imaging and agglomerative hierarchical clustering techniques to evaluate and rank physiological performance of wheat genotypes on sodic soil

S Das, J Christopher, A Apan, MR Choudhury… - ISPRS Journal of …, 2021 - Elsevier
Sodicity is a major soil constraint in many arid and semi-arid regions worldwide, including
Australia, which adversely affects the ability of crops to take up water and nutrients from the …

The robust and efficient Machine learning model for smart farming decisions and allied intelligent agriculture decisions

SK Apat, J Mishra, KS Raju, N Padhy - Journal of Integrated …, 2022 - pubs.iscience.in
Abstract Crop Yield Prediction is essential in today's rapidly changing agricultural market
(CYP). Accurate prediction relies on machine learning algorithms and selected features. Any …

Multispectral cameras and machine learning integrated into portable devices as clay prediction technology

GA Helfer, JLV Barbosa, D Alves, AB da Costa… - Journal of Sensor and …, 2021 - mdpi.com
The present work proposed a low-cost portable device as an enabling technology for
agriculture using multispectral imaging and machine learning in soil texture. Clay is an …

A survey on deep learning applications in wheat phenoty**

A Zaji, Z Liu, G **ao, JS Sangha, Y Ruan - Applied Soft Computing, 2022 - Elsevier
Precision farming has become a hot research topic in recent years due to the advancement
of sensing technologies, increased computer performance, and advanced deep learning …

Machine learning modeling of wine sensory profiles and color of vertical vintages of pinot noir based on chemical fingerprinting, weather and management data

S Fuentes, DD Torrico, E Tongson, C Gonzalez Viejo - Sensors, 2020 - mdpi.com
Important wine quality traits such as sensory profile and color are the product of complex
interactions between the soil, grapevine, the environment, management, and winemaking …