Comparison of influential input variables in the deep learning modeling of sunflower grain yields under normal and drought stress conditions
Published 2023 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Comparison of influential input variables in the deep learning modeling of sunflower grain yields under normal and drought stress conditions
Authors
Keywords
-
Journal
FIELD CROPS RESEARCH
Volume 303, Issue -, Pages 109145
Publisher
Elsevier BV
Online
2023-09-30
DOI
10.1016/j.fcr.2023.109145
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Evaluation of Introgressed Lines of Sunflower (Helianthus annuus L.) under Contrasting Water Treatments
- (2023) Muhammad Mubashar Hussain et al. Agriculture-Basel
- Maternal drought stress induces abiotic stress tolerance to the progeny at the germination stage in sunflower
- (2022) Baptiste Vancostenoble et al. ENVIRONMENTAL AND EXPERIMENTAL BOTANY
- Mitigating the Multicollinearity Problem and Its Machine Learning Approach: A Review
- (2022) Jireh Yi-Le Chan et al. Mathematics
- Beyond addressing multicollinearity: Robust quantitative analysis and machine learning in international business research
- (2022) Thomas Lindner et al. JOURNAL OF INTERNATIONAL BUSINESS STUDIES
- Prediction of sunflower grain yield under normal and salinity stress by RBF, MLP and, CNN models
- (2022) Sanaz Khalifani et al. INDUSTRIAL CROPS AND PRODUCTS
- Mitigating Drought Stress in Sunflower (Helianthus annuus L.) Through Exogenous Application of β-Aminobutyric Acid
- (2021) Allah Wasaya et al. Journal of Soil Science and Plant Nutrition
- Application of Machine Learning Algorithms in Plant Breeding: Predicting Yield From Hyperspectral Reflectance in Soybean
- (2021) Mohsen Yoosefzadeh-Najafabadi et al. Frontiers in Plant Science
- The Application of Multiple Linear Regression and Artificial Neural Network Models for Yield Prediction of Very Early Potato Cultivars before Harvest
- (2021) Magdalena Piekutowska et al. Agronomy-Basel
- Wheat physiology predictor: predicting physiological traits in wheat from hyperspectral reflectance measurements using deep learning
- (2021) Robert T. Furbank et al. Plant Methods
- Exploration of Machine Learning Approaches for Paddy Yield Prediction in Eastern Part of Tamilnadu
- (2021) Vinson Joshua et al. Agronomy-Basel
- Remote sensing and machine learning for crop water stress determination in various crops: a critical review
- (2020) Shyamal S. Virnodkar et al. PRECISION AGRICULTURE
- Winter Wheat Yield Prediction at County Level and Uncertainty Analysis in Main Wheat-Producing Regions of China with Deep Learning Approaches
- (2020) Xinlei Wang et al. Remote Sensing
- Drought Tolerance Strategies in Plants: A Mechanistic Approach
- (2020) Muhammad Ilyas et al. JOURNAL OF PLANT GROWTH REGULATION
- A deep learning approach for hydrological time-series prediction: A case study of Gilgit river basin
- (2020) Dostdar Hussain et al. Earth Science Informatics
- Using Artificial Neural Networks and Remotely Sensed Data to Evaluate the Relative Importance of Variables for Prediction of Within-Field Corn and Soybean Yields
- (2020) Angela Kross et al. Remote Sensing
- Response of Plants to Water Stress: A Meta-Analysis
- (2020) Yuan Sun et al. Frontiers in Plant Science
- Inspection and Classification of Semiconductor Wafer Surface Defects Using CNN Deep Learning Networks
- (2020) Jong-Chih Chien et al. Applied Sciences-Basel
- Sunflower growth and yield response to sewage sludge application under contrasting water availability conditions
- (2020) Spyridon D. Koutroubas et al. INDUSTRIAL CROPS AND PRODUCTS
- Machine Learning for Plant Breeding and Biotechnology
- (2020) Mohsen Niazian et al. Agriculture-Basel
- Assessing the mechanisms underlying sunflower grain weight and oil content responses to temperature during grain filling
- (2020) Patricia Angeloni et al. FIELD CROPS RESEARCH
- Deep convolutional neural networks for rice grain yield estimation at the ripening stage using UAV-based remotely sensed images
- (2019) Qi Yang et al. FIELD CROPS RESEARCH
- Multicriteria Prediction and Simulation of Winter Wheat Yield Using Extended Qualitative and Quantitative Data Based on Artificial Neural Networks
- (2019) Gniewko Niedbała et al. Applied Sciences-Basel
- County-Level Soybean Yield Prediction Using Deep CNN-LSTM Model
- (2019) Jie Sun et al. SENSORS
- ASAP: A new global early warning system to detect anomaly hot spots of agricultural production for food security analysis
- (2018) Felix Rembold et al. AGRICULTURAL SYSTEMS
- Drought stress in sunflower: Physiological effects and its management through breeding and agronomic alternatives
- (2018) Mubshar Hussain et al. AGRICULTURAL WATER MANAGEMENT
- A review of the use of convolutional neural networks in agriculture
- (2018) A. Kamilaris et al. JOURNAL OF AGRICULTURAL SCIENCE
- Recent advances in convolutional neural networks
- (2018) Jiuxiang Gu et al. PATTERN RECOGNITION
- A review of the use of convolutional neural networks in agriculture
- (2018) A. Kamilaris et al. JOURNAL OF AGRICULTURAL SCIENCE
- The effect of tuning, feature engineering, and feature selection in data mining applied to rainfed sugarcane yield modelling
- (2016) Felipe F. Bocca et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Polarimetric SAR Image Classification Using Deep Convolutional Neural Networks
- (2016) Yu Zhou et al. IEEE Geoscience and Remote Sensing Letters
- Machine Learning for High-Throughput Stress Phenotyping in Plants
- (2016) Arti Singh et al. TRENDS IN PLANT SCIENCE
- Seed yield prediction of sesame using artificial neural network
- (2015) Samad Emamgholizadeh et al. EUROPEAN JOURNAL OF AGRONOMY
- A stress-responsive NAC transcription factor SNAC3 confers heat and drought tolerance through modulation of reactive oxygen species in rice
- (2015) Yujie Fang et al. JOURNAL OF EXPERIMENTAL BOTANY
- Attribute Selection Impact on Linear and Nonlinear Regression Models for Crop Yield Prediction
- (2014) Alberto Gonzalez-Sanchez et al. TheScientificWorldJOURNAL
- Antioxidant capacity, photosynthetic characteristics and water relations of sunflower (Helianthus annuus L.) cultivars in response to drought stress
- (2013) Mokhtar Ghobadi et al. INDUSTRIAL CROPS AND PRODUCTS
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now