A machine learning approach for estimating forage maize yield and quality in NW Spain by Silverio García-Cortés, Agustín Menéndez-Díaz, María José Bande-Castro, Alfonso Carballal-Samalea, Adela Martínez-Fernández, Jose Alberto Oliveira-Prendes

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Interpretable Machine Learning for Legume Yield Prediction Using Satellite Remote Sensing Data by Theodoros Petropoulos, Lefteris Benos, Remigio Berruto, Gabriele Miserendino, Vasso Marinoudi, Patrizia Busato, Chrysostomos Zisis, Dionysis Bochtis

“…Accurate crop yield prediction is vital towards optimizing agricultural productivity. …”
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Remote sensing and TerraClimate datasets for wheat yield prediction using machine learning by Alireza Araghi, Andre Daccache

“…This study leverages satellite imagery and a gridded climate dataset (TerraClima) with machine learning (ML) to predict wheat yields in Mashhad County (Northeast Iran). …”
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Crop yield prediction in agriculture: A comprehensive review of machine learning and deep learning approaches, with insights for future research and sustainability by Md. Abu Jabed, Masrah Azrifah Azmi Murad

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HiCLR: Knowledge-Induced Hierarchical Contrastive Learning with Retrosynthesis Prediction Yields a Reaction Foundation Model by Jialu Wu, Yiheng Zhu, Xiaorui Wang, Yitong Li, Mingze Yin, Tianyue Wang, Yuqiang Han, Yu Kang, Yafeng Deng, Jian Wu, Chang-Yu Hsieh, Tingjun Hou

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Impact of Advanced Agriculture Technologies and Energy Consumption on Crop Yields in Modern Agriculture Using Deep Learning Techniques by Khan Baz, Zhu Zhen, Hashmat Ali

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Incorporating soil moisture data into a machine learning framework improved the predictive accuracy of corn yields in the U.S. by Bishwoyog Bhattarai, Zachary Leasor, André Fróes de Borja Reis

“…Leveraging machine learning (ML) techniques capable of handling large-scale datasets offers a promising alternative for uncovering hidden patterns and generating actionable insights to improve crop yield. …”
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Precision agriculture for improving crop yield predictions: a literature review by Sarmistha Saha, Olga D. Kucher, Aleksandra O. Utkina, Nazih Y. Rebouh

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Crop Yield Prediction: Data Structure and Ai-Powered Methods by V. K. Kalichkin, K. Yu. Maksimovich, O. A. Aleshchenko, V. V. Aleshchenko

Subjects: “…crop yield prediction…”
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Utility of Domain Adaptation for Biomass Yield Forecasting by Jonathan M. Vance, Bryan Smith, Abhishek Cherukuru, Khaled Rasheed, Ali Missaoui, John A. Miller, Frederick Maier, Hamid Arabnia

“…Previous work used machine learning (ML) to estimate past and current alfalfa yields and showed that domain adaptation (DA) with data synthesis shows promise in classifying yields as high, medium, or low. …”
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An explainable AI-based hybrid machine learning model for interpretability and enhanced crop yield prediction by Anuradha Yenkikar, Ved Prakash Mishra, Manish Bali, Tabassum Ara

“…Key crops like rice are essential for food security, making higher yields crucial for sustainability. The use of machine learning (ML) in crop yield prediction has significantly improved forecast accuracy. …”
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Price Forecast of Treasury Bond Market Yield: Optimize Method Based on Deep Learning Model by Weiying Ping, Yuwen Hu, Liangqing Luo

Subjects: “…Market yield of treasury bond…”
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Estimation of the yield and green water footprint of rainfed wheat based on remote sensing and machine learning by Mojgan Ahmadi, Hadi Ramezani Etedali, Abbass Kaviani, Alireza Tavakoli

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Soybean Lodging Classification and Yield Prediction Using Multimodal UAV Data Fusion and Deep Learning by Xingmei Xu, Yushi Fang, Guangyao Sun, Yong Zhang, Lei Wang, Chen Chen, Lisuo Ren, Lei Meng, Yinghui Li, Lijuan Qiu, Yan Guo, Helong Yu, Yuntao Ma

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Human limits in machine learning: prediction of potato yield and disease using soil microbiome data by Rosa Aghdam, Xudong Tang, Shan Shan, Richard Lankau, Claudia Solís-Lemus

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Integrating WOFOST and Deep Learning for Winter Wheat Yield Estimation in the Huang-Huai-Hai Plain by Yachao Zhao, Xin Du, Jingyuan Xu, Qiangzi Li, Yuan Zhang, Hongyan Wang, Sifeng Yan, Shuguang Gong, Haoxuan Hu

“…In this study, a yield estimation framework was developed by integrating Sentinel-2 and Landsat-8 satellite data with the WOFOST crop growth model and deep learning techniques. …”
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Machine learning on multi‐spectral imagery to estimate nutrient yield of mixed‐species cover crops by Tulsi P. Kharel, Heather L. Tyler, Partson Mubvumba, Yanbo Huang, Ammar B. Bhandari, Reginald S. Fletcher, Saseendran Anapalli, Deepak R. Joshi, Alemu Mengistu, Girma Birru, Kabindra Adhikari, Madhav Dhakal, Mahesh L. Maskey, Krishna N. Reddy, David E. Clay

“…The chlorophyll absorption ratio index and the normalized difference vegetation index closely followed the biomass nutrients N, P, and K combined yield (Bio_NPK) trend. Machine learning algorithms random forest (RF) and partial least square (PLS) regression were better for biomass (R2 = 0.74 with RF) and N% (R2 = 0.72 with PLS) prediction compared to the Bio_NPK prediction. …”
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Evaluation of Machine Learning Models for Estimating Grassland Pasture Yield Using Landsat-8 Imagery by Linming Huang, Fen Zhao, Guozheng Hu, Hasbagan Ganjurjav, Rihan Wu, Qingzhu Gao

Subjects: “…pasture yield…”
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Ensemble learning-based crop yield estimation: a scalable approach for supporting agricultural statistics by Patric Brandt, Florian Beyer, Peter Borrmann, Markus Möller, Heike Gerighausen

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Satellite imagery, big data, IoT and deep learning techniques for wheat yield prediction in Morocco by Abdelouafi Boukhris, Antari Jilali, Abderrahmane Sadiq

“…We are the first paper that has combined spatial data and temporal data to predict crop yield based on deep learning algorithms, unlike other works that uses only remote sensing data or temporal data. …”
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