Prediction of Pea (Pisum sativum L.) Seeds Yield Using Artificial Neural Networks

P Hara, M Piekutowska, G Niedbała - Agriculture, 2023 - mdpi.com
A sufficiently early and accurate prediction can help to steer crop yields more consciously,
resulting in food security, especially with an expanding world population. Additionally …

Prediction of Protein Content in Pea (Pisum sativum L.) Seeds Using Artificial Neural Networks

P Hara, M Piekutowska, G Niedbała - Agriculture, 2022 - mdpi.com
Pea (Pisum sativum L.) is a legume valued mainly for its high seed protein content. The
protein content of pea is characterized by a high lysine content and low allergenicity. This …

Evaluation of various machine learning prediction methods for particulate matter in Kuwait

A Alsaber, R Alsahli, A Al-Sultan, I Abu Doush… - International Journal of …, 2023 - Springer
Air pollution poses a serious threat to public health and for the environment, thus predicting
air quality is very crucial for the health and well-being of individuals and the environment …

Statistical and machine learning models for location-specific crop yield prediction using weather indices

MK Debnath - International Journal of Biometeorology, 2024 - Springer
Crop yield prediction gains growing importance for all stakeholders in agriculture. Since the
growth and development of crops are fully connected with many weather factors, it is …

Influence of Silicic Acid Foliar Spray on Foraging Behaviour of Bee Pollinators and Yield of Rapeseed

R Karthik, MK Deka, S Ajith, M Laxmanarayanan… - Silicon, 2024 - Springer
Silicic acid (SA) is an important source of silicon (Si), a quasi-essential element inducing
growth, yield and abiotic and biotic stress tolerance in crops. SA was obtained from ReXil …

Development of a fabric classification system using drapability and tactile characteristics

S Lee, Y Han, C Yun - Fashion and Textiles, 2024 - Springer
When producing clothing using virtual fitting technology or purchasing textile and clothing
products online, it is challenging to make judgments or communicate information about …

Predicting rice yield based on weather variables using multiple linear, neural networks, and penalized regression models

P Setiya, A Satpathi, AS Nain - Theoretical and Applied Climatology, 2023 - Springer
Rice is one of the most important cereal foods not only for India but also for the world. The
production of crop depends upon the favorable climatic conditions. Farmers' access to more …

Crop Yield Estimation using Improved Salp Swarm Algorithm based Feature Selection

DJ Reddy, MR Kumar - Journal of Electrical Systems, 2024 - search.proquest.com
Crop yield estimation is the art of yield prediction before harvest and it is essential for
planning and making conclusive agricultural policies. The forecasting of crop yield is …

[PDF][PDF] Prediction of Pea (Pisum sativum L.) Seeds Yield Using Artificial Neural Networks. Agriculture 2023, 13, 661

P Hara, M Piekutowska, G Niedbała - 2023 - researchgate.net
A sufficiently early and accurate prediction can help to steer crop yields more consciously,
resulting in food security, especially with an expanding world population. Additionally …

Weather-Based Rice Crop Yield Forecasting using Different Regression Techniques & Neural Network Approach for Prayagraj Region

NK Singh, S Rawat, S Gautam - International Journal of …, 2023 - archive.sdpublishers.com
Rice crop yield data and weather data were considered in this study, covering the past
twenty-nine years (1991-2019) in Prayagraj District, Uttar Pradesh. The data was sourced …