Autonomous Drone-Based Pollination Systems for Enhancing Crop Yield in Orchards Using IoT and Machine Learning Optimization by Khan Roohee, Lalnunthari Banti

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Advanced prediction of rice yield gaps under climate uncertainty using machine learning techniques in Eastern India by Satiprasad Sahoo, Chiranjit Singha, Ajit Govind

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Soybean Yield Estimation Using Improved Deep Learning Models With Integrated Multisource and Multitemporal Remote Sensing Data by Jian Li, Junrui Kang, Ji Qi, Jian Lu, Hongkun Fu, Baoqi Liu, Xinglei Lin, Jiawei Zhao, Hengxu Guan, Jing Chang, Zhihan Liu

Subjects: “…Deep learning (DL)…”
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Deep learning framework for fruit counting and yield mapping in tart cherry using YOLOv8 and YOLO11 by Anderson L.S. Safre, Alfonso Torres-Rua, Brent L. Black, Sierra Young

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Early Yield Prediction of Oilseed Rape Using UAV-Based Hyperspectral Imaging Combined with Machine Learning Algorithms by Hongyan Zhu, Chengzhi Lin, Zhihao Dong, Jun-Li Xu, Yong He

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The impact of spatiotemporal variability of environmental conditions on wheat yield forecasting using remote sensing data and machine learning by Keltoum Khechba, Mariana Belgiu, Ahmed Laamrani, Alfred Stein, Abdelhakim Amazirh, Abdelghani Chehbouni

“…This study aims to assess the impact of spatial and temporal heterogeneity of environmental conditions on wheat yield forecasting using machine learning models. …”
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Machine learning algorithms for maize yield prediction with multispectral imagery: Assessing robustness across varied growing environments by Bala Ram Sapkota, Gurjinder S. Baath, K. Colton Flynn, Kabindra Adhikari, Chad Hajda, Douglas R. Smith

“…This study investigates the potential use of canopy spectral reflectance, directly applied in conjunction with machine learning (ML) to address these limitations and produce more consistent and reliable yield predictions. …”
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Yield prediction, pest and disease diagnosis, soil fertility mapping, precision irrigation scheduling, and food quality assessment using machine learning and deep learning algorithms by S. Ajith, S. Vijayakumar, N. Elakkiya

“…Artificial intelligence, particularly machine learning and deep learning, is revolutionizing agricultural practices by enabling data-driven, precise, and sustainable solutions. …”
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Explainability of Subfield Level Crop Yield Prediction Using Remote Sensing by Hiba Najjar, Miro Miranda, Marlon Nuske, Ribana Roscher, Andreas Dengel

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Prediction of elastic modulus, yield strength, and tensile strength in biocompatible titanium alloys by Marković G., Ružić J., Sokić M., Milojkov D., Manojlović V.D.

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Mapping global yields of four major crops at 5-minute resolution from 1982 to 2015 using multi-source data and machine learning by Juan Cao, Zhao Zhang, Xiangzhong Luo, Yuchuan Luo, Jialu Xu, Jun Xie, Jichong Han, Fulu Tao

“…Abstract Accurate, historical, and continuous global crop yield data are essential for assessing risks to the global food system. …”
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Prediction of Crop Yield by Support Vector Machine Coupled with Deep Learning Algorithm Procedures in Lower Kulfo Watershed of Ethiopia by Abebe Temesgen Ayalew, Tarun Kumar Lohani

“…The support vector machine (SVM) was applied as a machine learning procedure, whereas long short-term memory (LSTM) and the recurrent neural network (RNN) were considered as deep learning procedures. …”
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Dynamic gating-enhanced deep learning model with multi-source remote sensing synergy for optimizing wheat yield estimation by Jian Li, Jian Li, Junrui Kang, Junrui Kang, Jian Lu, Jian Lu, Hongkun Fu, Hongkun Fu, Zheng Li, Zheng Li, Baoqi Liu, Xinglei Lin, Xinglei Lin, Jiawei Zhao, Hengxu Guan, He Liu, Zhihan Liu

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An assessment of optimizing biofuel yield percentage using K-fold integrated machine learning models for a sustainable future by Krishnamoorthy Ramalingam, Mohd. Zulkifly Abdullah, Perumal Venkatesan Elumalai, Allam Sangeetha, Xu Yong, Nasim Hasan, Wei Shangzhi

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Leveraging Multi-Omics Data with Machine Learning to Predict Grain Yield in Small vs. Big Plot Wheat Trials by Jordan McBreen, Md Ali Babar, Diego Jarquin, Yiannis Ampatzidis, Naeem Khan, Sudip Kunwar, Janam Prabhat Acharya, Samuel Adewale, Gina Brown-Guedira

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Predictive modelling of hexagonal boron nitride nanosheets yield through machine and deep learning: An ultrasonic exfoliation parametric evaluation by Jerrin Joy Varughese, Sreekanth M․S․

“…The study extends beyond optimizing exfoliation parameters by employing machine learning (ML) and deep learning (DL) techniques to forecast the yield of hBNNs. …”
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Deep-Transfer-Learning Strategies for Crop Yield Prediction Using Climate Records and Satellite Image Time-Series Data by Abhasha Joshi, Biswajeet Pradhan, Subrata Chakraborty, Renuganth Varatharajoo, Shilpa Gite, Abdullah Alamri

Subjects: “…crop yield prediction…”
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Predicting apheresis yield and factors affecting peripheral blood stem cell harvesting using a machine learning model by Jing Qi, Yinchu Chen, Xiaoke Jin, Ran Wang, Nana Wang, Jiawei Yan, Chen Huang, Jun Huang, Yuanfeng Wei, Faqin Xie, Zhengzhi Yu, Dongping Huang

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Advancing pearl millet yield forecasting: Comparative analysis of individual and ensemble machine learning approaches over Rajasthan, India. by Ahmad Alsaber, Parul Setiya, Anurag Satpathi, Abrar Aljamaan, Jiazhu Pan

“…Rajasthan, a state in India, emerged as the top producer of pearl millet. This study enhances yield forecasting for pearl millet using machine learning models across nine districts viz. …”
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Feature engineering on climate data with machine learning to understand time-lagging effects in pasture yield predictionGitHub by Thirunavukarasu Balasubramaniam, Wathsala Anupama Mohotti, Kenneth Sabir, Richi Nayak

“…This time-lagging effect complicates the development of machine-learning models that can learn the temporal dependencies to predict pasture yield. …”
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