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
Machine learning approach for satellite-based subfield canola yield prediction using floral phenology metrics and soil parameters
Sign Up to like & getrecommendations! Published in 2024 at "Precision Agriculture"
DOI: 10.1007/s11119-024-10116-1
Abstract: Early monitoring of within-field yield variability and forecasting yield potential is critical for farmers and other key stakeholders such as policymakers. Remote sensing techniques are progressively being used in yield prediction studies due to easy… read more here.
Keywords: topography; yield; yield prediction; canola yield ... See more keywords
Accuracy and robustness of a plant-level cabbage yield prediction system generated by assimilating UAV-based remote sensing data into a crop simulation model
Sign Up to like & getrecommendations! Published in 2024 at "Precision Agriculture"
DOI: 10.1007/s11119-024-10192-3
Abstract: In-season crop growth and yield prediction at high spatial resolution are essential for informing decision-making for precise crop management, logistics and market planning in horticultural crop production. This research aimed to establish a plant-level cabbage… read more here.
Keywords: cabbage yield; yield prediction; crop; yield ... 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
Exploring BERT for Reaction Yield Prediction: Evaluating the Impact of Tokenization, Molecular Representation, and Pretraining Data Augmentation
Sign Up to like & getrecommendations! Published in 2025 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.5c00359
Abstract: Predicting reaction yields in synthetic chemistry remains a significant challenge. This study systematically evaluates the impact of tokenization, molecular representation, pretraining data, and adversarial training on a BERT-based model for yield prediction of Buchwald-Hartwig and… read more here.
Keywords: reaction; pretraining data; chemistry; yield prediction ... 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
Crop yield prediction using ensemble learning with effective data analytics
Sign Up to like & getrecommendations! Published in 2025 at "Engineering Computations"
DOI: 10.1108/ec-02-2025-0095
Abstract: Accurate crop yield prediction (CYP) is essential for enhancing agricultural productivity, ensuring food security and enabling sustainable resource management. Machine learning (ML) algorithms have become popular in CYP because they can estimate crop production based… read more here.
Keywords: yield prediction; data analytics; crop; 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