Research graph
References from Predicting crop yield and nutrient needs using explainable artificial intelligence. Local targets link to admitted publications; unresolved targets remain external evidence.
Options for calibrating CERES-maize genotype specific parameters under data-scarce environments
10.1371/journal.pone.0200118 · 2019 · External reference
Explainable artificial intelligence (xai): concepts, taxonomies, opportunities and challenges toward responsible ai
10.1016/j.inffus.2019.12.012 · 2020 · External reference
Agricultural decision system based on advanced machine learning models for yield prediction: case of east african countries
10.1016/j.atech.2022.100048 · 2022 · External reference
Detection of nutrition deficiencies in plants using proximal images and machine learning: a review
10.1016/j.compag.2019.04.035 · 2019 · External reference
Crop yield prediction with efficient use of fertilizers
10.1007/978-981-16-3690-5_87 · 2022 · External reference
Progress in research on site-specific nutrient management for smallholder farmers in sub-saharan africa
10.1016/j.fcr.2022.108503 · 2022 · External reference
African agriculture in 50years: smallholders in a rapidly changing world?
10.1016/j.worlddev.2013.10.001 · 2014 · External reference
Predicting site-specific economic optimal nitrogen rate using machine learning methods and on-farm precision experimentation
2023 · External reference
The role of agriculture in african development
10.1016/j.worlddev.2009.06.011 · 2010 · External reference
Gradient boosting for yield prediction of elite maize hybrid zhengdan 958
10.1371/journal.pone.0315493 · 2024 · External reference
The assessment of soil variables relative importance for cereal yield prediction under rainfed cropping system in morocco
10.1016/j.atech.2025.100950 · 2025 · External reference
Machine learning in nutrient management: a review
2023 · External reference
From prediction to prescription: intelligent decision support for variable rate fertilization
1998 · External reference
An explainable deep machine vision framework for plant stress phenotyping
10.1073/pnas.1716999115 · 2018 · External reference
Principal challenges confronting smallholder agriculture in sub-saharan africa
10.1016/j.worlddev.2010.06.002 · 2010 · External reference
A comprehensive review on automation in agriculture using artificial intelligence
2019 · External reference
A review on the practice of big data analysis in agriculture
10.1016/j.compag.2017.09.037 · 2017 · External reference
Deep learning in agriculture: a survey
10.1016/j.compag.2018.02.016 · 2018 · External reference
Unresolved reference
External reference
Crop yield prediction using deep neural networks: a comprehensive review and case study
2023 · External reference
Machine learning in agriculture: a review
10.3390/s18082674 · 2018 · External reference
Machine learning in agriculture: a review
10.3390/s18082674 · 2018 · External reference
Explainable artificial intelligence for agriculture and crop yield prediction: a survey
2022 · External reference
Sub-saharan africa: the state of smallholders in agriculture
2011 · External reference
Explainable ai (xai) in agriculture: concepts, techniques, and applications
2023 · External reference
Using deep learning for image-based plant disease detection
10.3389/fpls.2016.01419 · 2016 · External reference
Agriculture and environmental degradation in africa: the role of income
10.1016/j.scitotenv.2019.07.129 · 2019 · External reference
Computer vision and artificial intelligence in precision agriculture for grain crops: a systematic review
10.1016/j.compag.2018.08.001 · 2018 · External reference
Machine learning for large-scale crop yield forecasting
10.1016/j.agsy.2020.103016 · 2021 · External reference
Agro based crop and fertilizer recommendation system using machine learning
2020 · External reference
Examining the interplay between artificial intelligence and the agrifood industry
2022 · External reference
Unresolved reference
2010 · External reference
Machine learning: algorithms, real-world applications and research directions
10.1007/s42979-021-00592-x · 2021 · External reference
Sociotechnical context and agroecological transition for smallholder farms in Benin and Burkina Faso
10.3390/agronomy10091447 · 2020 · External reference
Crop yield prediction using machine learning: a systematic literature review
10.1016/j.compag.2020.105709 · 2020 · External reference
Unresolved reference
2020 · External reference
A deep learning-based approach for automated yellow rust disease detection from high-resolution hyperspectral uav imagery
10.3390/rs11131554 · 2019 · External reference
Crop yield prediction with efficient use of fertilizers
10.1007/978-981-16-3690-5_87 · ExternalCitation · doi-reference
Machine learning: algorithms, real-world applications and research directions
10.1007/s42979-021-00592-x · ExternalCitation · doi-reference
Machine learning for large-scale crop yield forecasting
10.1016/j.agsy.2020.103016 · ExternalCitation · doi-reference
Agricultural decision system based on advanced machine learning models for yield prediction: case of east african countries
10.1016/j.atech.2022.100048 · ExternalCitation · doi-reference
The assessment of soil variables relative importance for cereal yield prediction under rainfed cropping system in morocco
10.1016/j.atech.2025.100950 · ExternalCitation · doi-reference
A review on the practice of big data analysis in agriculture
10.1016/j.compag.2017.09.037 · ExternalCitation · doi-reference
Deep learning in agriculture: a survey
10.1016/j.compag.2018.02.016 · ExternalCitation · doi-reference
Computer vision and artificial intelligence in precision agriculture for grain crops: a systematic review
10.1016/j.compag.2018.08.001 · ExternalCitation · doi-reference
Detection of nutrition deficiencies in plants using proximal images and machine learning: a review
10.1016/j.compag.2019.04.035 · ExternalCitation · doi-reference
Crop yield prediction using machine learning: a systematic literature review
10.1016/j.compag.2020.105709 · ExternalCitation · doi-reference
Progress in research on site-specific nutrient management for smallholder farmers in sub-saharan africa
10.1016/j.fcr.2022.108503 · ExternalCitation · doi-reference
Explainable artificial intelligence (xai): concepts, taxonomies, opportunities and challenges toward responsible ai
10.1016/j.inffus.2019.12.012 · ExternalCitation · doi-reference
Agriculture and environmental degradation in africa: the role of income
10.1016/j.scitotenv.2019.07.129 · ExternalCitation · doi-reference
The role of agriculture in african development
10.1016/j.worlddev.2009.06.011 · ExternalCitation · doi-reference
Principal challenges confronting smallholder agriculture in sub-saharan africa
10.1016/j.worlddev.2010.06.002 · ExternalCitation · doi-reference
African agriculture in 50years: smallholders in a rapidly changing world?
10.1016/j.worlddev.2013.10.001 · ExternalCitation · doi-reference
An explainable deep machine vision framework for plant stress phenotyping
10.1073/pnas.1716999115 · ExternalCitation · doi-reference
Options for calibrating CERES-maize genotype specific parameters under data-scarce environments
10.1371/journal.pone.0200118 · ExternalCitation · doi-reference
Gradient boosting for yield prediction of elite maize hybrid zhengdan 958
10.1371/journal.pone.0315493 · ExternalCitation · doi-reference
Using deep learning for image-based plant disease detection
10.3389/fpls.2016.01419 · ExternalCitation · doi-reference
Sociotechnical context and agroecological transition for smallholder farms in Benin and Burkina Faso
10.3390/agronomy10091447 · ExternalCitation · doi-reference
A deep learning-based approach for automated yellow rust disease detection from high-resolution hyperspectral uav imagery
10.3390/rs11131554 · ExternalCitation · doi-reference
Machine learning in agriculture: a review
10.3390/s18082674 · ExternalCitation · doi-reference
