Evaluation of different gridded rainfall datasets for rainfed wheat yield prediction in an arid environment
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Biometeorology"
DOI: 10.1007/s00484-018-1555-x
Abstract: The accuracy of daily output of satellite and reanalysis data is quite crucial for crop yield prediction. This study has evaluated the performance of APHRODITE (Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation), PERSIANN (Rainfall Estimation… read more here.
Keywords: yield prediction; ground observed; precipitation; rainfed wheat ... See more keywords
Efficient agricultural yield prediction using metaheuristic optimized artificial neural network using Hadoop framework
Sign Up to like & getrecommendations! Published in 2020 at "Soft Computing"
DOI: 10.1007/s00500-020-04707-z
Abstract: The low-resolution imagery of satellite is used extensively for monitoring crops and forecasting of yield which has a major role to play in the operational systems. A combination of high levels of temporal frequency along… read more here.
Keywords: yield prediction; yield; agricultural yield; neural network ... See more keywords
Linking process-based potato models with light reflectance data: Does model complexity enhance yield prediction accuracy?
Sign Up to like & getrecommendations! Published in 2017 at "European Journal of Agronomy"
DOI: 10.1016/j.eja.2016.10.008
Abstract: Data acquisition for parameterization is one of the most important limitations for the use of potato crop growth models. Non-destructive techniques such as remote sensing for gathering required data could circumvent this limitation. Our goal… read more here.
Keywords: model; yield prediction; reflectance data; complexity ... See more keywords
Soybean yield prediction from UAV using multimodal data fusion and deep learning
Sign Up to like & getrecommendations! Published in 2020 at "Remote Sensing of Environment"
DOI: 10.1016/j.rse.2019.111599
Abstract: Abstract Preharvest crop yield prediction is critical for grain policy making and food security. Early estimation of yield at field or plot scale also contributes to high-throughput plant phenotyping and precision agriculture. New developments in… read more here.
Keywords: data fusion; yield prediction; yield; fusion ... See more keywords
Machine Learning C–N Couplings: Obstacles for a General-Purpose Reaction Yield Prediction
Sign Up to like & getrecommendations! Published in 2023 at "ACS Omega"
DOI: 10.1021/acsomega.2c05546
Abstract: Pd-catalyzed C–N couplings are commonplace in academia and industry. Despite their significance, finding suitable reaction conditions leading to a high yield, for instance, remains a challenging and time-consuming task which usually requires screening over many… read more here.
Keywords: reaction; reaction yield; machine learning; yield prediction ... See more keywords
Winter wheat yield prediction using convolutional neural networks from environmental and phenological data
Sign Up to like & getrecommendations! Published in 2022 at "Scientific Reports"
DOI: 10.1038/s41598-022-06249-w
Abstract: Crop yield forecasting depends on many interactive factors, including crop genotype, weather, soil, and management practices. This study analyzes the performance of machine learning and deep learning methods for winter wheat yield prediction using an… read more here.
Keywords: wheat yield; yield; prediction; yield prediction ... See more keywords
Ensemble machine learning techniques using computer simulation data for wild blueberry yield prediction
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3181970
Abstract: Precision agriculture is a challenging task to achieve. Several studies have been conducted to forecast agricultural yields using machine learning algorithms (MLA), but few studies have used ensemble machine learning algorithms (EMLA). In the current… read more here.
Keywords: blueberry yield; machine learning; wild blueberry; prediction ... See more keywords
A Bayesian Domain Adversarial Neural Network for Corn Yield Prediction
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3211444
Abstract: Corn is the most widely grown crop in the U.S. and makes up a significant part of the American diet. Under the pressure of feeding a growing population, accurate and timely estimation of corn yield… read more here.
Keywords: domain; yield prediction; corn; corn yield ... See more keywords
Multisource Maximum Predictor Discrepancy for Unsupervised Domain Adaptation on Corn Yield Prediction
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3247343
Abstract: Recently, with the advent of satellite missions and artificial intelligence techniques, supervised machine learning (ML) methods have been more and more used for analyzing remote sensing (RS) observation data for crop yield prediction. However, due… read more here.
Keywords: multisource; domain; yield prediction; discrepancy ... See more keywords
Yield prediction by machine learning from UAS-based mulit-sensor data fusion in soybean
Sign Up to like & getrecommendations! Published in 2020 at "Plant Methods"
DOI: 10.1186/s13007-020-00620-6
Abstract: Background Nowadays, automated phenotyping of plants is essential for precise and cost-effective improvement in the efficiency of crop genetics. In recent years, machine learning (ML) techniques have shown great success in the classification and modelling… read more here.
Keywords: sensor; machine learning; yield prediction; yield ... See more keywords
The HADES Yield Prediction System – A Case Study on the Turkish Hazelnut Sector
Sign Up to like & getrecommendations! Published in 2021 at "Frontiers in Plant Science"
DOI: 10.3389/fpls.2021.665471
Abstract: Crop yield forecasting activities are essential to support decision making of farmers, private companies and public entities. While standard systems use georeferenced agro-climatic data as input to process-based simulation models, new trends entail the application… read more here.
Keywords: prediction system; hazelnut; yield prediction;