Application of artificial intelligence in food industry—a guideline

NR Mavani, JM Ali, S Othman, MA Hussain… - Food Engineering …, 2022 - Springer
Artificial intelligence (AI) has embodied the recent technology in the food industry over the
past few decades due to the rising of food demands in line with the increasing of the world …

Towards paddy rice smart farming: a review on big data, machine learning, and rice production tasks

R Alfred, JH Obit, CPY Chin, H Haviluddin, Y Lim - Ieee Access, 2021 - ieeexplore.ieee.org
Big Data (BD), Machine Learning (ML) and Internet of Things (IoT) are expected to have a
large impact on Smart Farming and involve the whole supply chain, particularly for rice …

Crop yield prediction based on Indian agriculture using machine learning

PS Nishant, PS Venkat, BL Avinash… - 2020 international …, 2020 - ieeexplore.ieee.org
In India, we all know that Agriculture is the backbone of the country. This paper predicts the
yield of almost all kinds of crops that are planted in India. This script makes novel by the …

Emerging trends in machine learning to predict crop yield and study its influential factors: A survey

N Bali, A Singla - Archives of computational methods in engineering, 2022 - Springer
Agriculture is one of the most crucial field contributing to the development of any nation. It
not only affects the economy of nation but also has impact on the world food grain statistics …

Dynamic neural network modelling of soil moisture content for predictive irrigation scheduling

O Adeyemi, I Grove, S Peets, Y Domun, T Norton - Sensors, 2018 - mdpi.com
Sustainable freshwater management is underpinned by technologies which improve the
efficiency of agricultural irrigation systems. Irrigation scheduling has the potential to …

Selection of independent variables for crop yield prediction using artificial neural network models with remote sensing data

P Hara, M Piekutowska, G Niedbała - Land, 2021 - mdpi.com
Knowing the expected crop yield in the current growing season provides valuable
information for farmers, policy makers, and food processing plants. One of the main benefits …

MMST-ViT: Climate Change-aware Crop Yield Prediction via Multi-Modal Spatial-Temporal Vision Transformer

F Lin, S Crawford, K Guillot, Y Zhang… - Proceedings of the …, 2023 - openaccess.thecvf.com
Precise crop yield prediction provides valuable information for agricultural planning and
decision-making processes. However, timely predicting crop yields remains challenging as …

An approach for prediction of crop yield using machine learning and big data techniques

K Palanivel, C Surianarayanan - International Journal of Computer …, 2019 - papers.ssrn.com
Agriculture is the primary source of livelihood which forms the backbone of our country.
Current challenges of water shortages, uncontrolled cost due to demand-supply, and …

Rice crop yield prediction in India using support vector machines

N Gandhi, LJ Armstrong, O Petkar… - … 13th International Joint …, 2016 - ieeexplore.ieee.org
Food production in India is largely dependent on cereal crops including rice, wheat and
various pulses. The sustainability and productivity of rice growing areas is dependent on …

Remote sensing-based estimation of rice yields using various models: A critical review

DMG dela Torre, J Gao… - Geo-Spatial Information …, 2021 - Taylor & Francis
Reliable estimation of region-wide rice yield is vital for food security and agricultural
management. Field-scale models have increased our understanding of rice yield and its …